Search results for: computer tasks
2063 Semiotics of the New Commercial Music Paradigm
Authors: Mladen Milicevic
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This presentation will address how the statistical analysis of digitized popular music influences the music creation and emotionally manipulates consumers.Furthermore, it will deal with semiological aspect of uniformization of musical taste in order to predict the potential revenues generated by popular music sales. In the USA, we live in an age where most of the popular music (i.e. music that generates substantial revenue) has been digitized. It is safe to say that almost everything that was produced in last 10 years is already digitized (either available on iTunes, Spotify, YouTube, or some other platform). Depending on marketing viability and its potential to generate additional revenue most of the “older” music is still being digitized. Once the music gets turned into a digital audio file,it can be computer-analyzed in all kinds of respects, and the similar goes for the lyrics because they also exist as a digital text file, to which any kin of N Capture-kind of analysis may be applied. So, by employing statistical examination of different popular music metrics such as tempo, form, pronouns, introduction length, song length, archetypes, subject matter,and repetition of title, the commercial result may be predicted. Polyphonic HMI (Human Media Interface) introduced the concept of the hit song science computer program in 2003.The company asserted that machine learning could create a music profile to predict hit songs from its audio features Thus,it has been established that a successful pop song must include: 100 bpm or more;an 8 second intro;use the pronoun 'you' within 20 seconds of the start of the song; hit the bridge middle 8 between 2 minutes and 2 minutes 30 seconds; average 7 repetitions of the title; create some expectations and fill that expectation in the title. For the country song: 100 bpm or less for a male artist; 14-second intro; uses the pronoun 'you' within the first 20 seconds of the intro; has a bridge middle 8 between 2 minutes and 2 minutes 30 seconds; has 7 repetitions of title; creates an expectation,fulfills it in 60 seconds.This approach to commercial popular music minimizes the human influence when it comes to which “artist” a record label is going to sign and market. Twenty years ago,music experts in the A&R (Artists and Repertoire) departments of the record labels were making personal aesthetic judgments based on their extensive experience in the music industry. Now, the computer music analyzing programs, are replacing them in an attempt to minimize investment risk of the panicking record labels, in an environment where nobody can predict the future of the recording industry.The impact on the consumers taste through the narrow bottleneck of the above mentioned music selection by the record labels,created some very peculiar effects not only on the taste of popular music consumers, but also the creative chops of the music artists as well. What is the meaning of this semiological shift is the main focus of this research and paper presentation.Keywords: music, semiology, commercial, taste
Procedia PDF Downloads 3932062 Applications of Evolutionary Optimization Methods in Reinforcement Learning
Authors: Rahul Paul, Kedar Nath Das
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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods
Procedia PDF Downloads 802061 Advanced Mouse Cursor Control and Speech Recognition Module
Authors: Prasad Kalagura, B. Veeresh kumar
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We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.Keywords: embedded ARM7 processor, mouse pointer control, voice recognition
Procedia PDF Downloads 5782060 Computer Server Virtualization
Authors: Pradeep M. C. Chand
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Virtual infrastructure initiatives often spring from data center server consolidation projects, which focus on reducing existing infrastructure “box count”, retiring older hardware or life-extending legacy applications. Server consolidation benefits result from a reduction in the overall number of systems and related recurring costs (power, cooling, rack space, etc.) and also helps in the reduction of heat to the environment.Keywords: server virtualization, data center, consolidation, project
Procedia PDF Downloads 5302059 A Comprehensive Study and Evaluation on Image Fashion Features Extraction
Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen
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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.Keywords: convolutional neural network, feature representation, image processing, machine modelling
Procedia PDF Downloads 1392058 Innovative Technologies Functional Methods of Dental Research
Authors: Sergey N. Ermoliev, Margarita A. Belousova, Aida D. Goncharenko
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Application of the diagnostic complex of highly informative functional methods (electromyography, reodentography, laser Doppler flowmetry, reoperiodontography, vital computer capillaroscopy, optical tissue oximetry, laser fluorescence diagnosis) allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment. Introduction. It is necessary to create a complex of innovative highly informative and safe functional diagnostic methods for improvement of the quality of patient treatment by the early detection of stomatologic diseases. The purpose of the present study was to investigate the etiology and pathogenesis of functional disorders identified in the pathology of hard tissue, dental pulp, periodontal, oral mucosa and chewing function, and the creation of new approaches to the diagnosis of dental diseases. Material and methods. 172 patients were examined. Density of hard tissues of the teeth and jaw bone was studied by intraoral ultrasonic densitometry (USD). Electromyographic activity of masticatory muscles was assessed by electromyography (EMG). Functional state of dental pulp vessels assessed by reodentography (RDG) and laser Doppler flowmetry (LDF). Reoperiodontography method (RPG) studied regional blood flow in the periodontal tissues. Microcirculatory vascular periodontal studied by vital computer capillaroscopy (VCC) and laser Doppler flowmetry (LDF). The metabolic level of the mucous membrane was determined by optical tissue oximetry (OTO) and laser fluorescence diagnosis (LFD). Results and discussion. The results obtained revealed changes in mineral density of hard tissues of the teeth and jaw bone, the bioelectric activity of masticatory muscles, regional blood flow and microcirculation in the dental pulp and periodontal tissues. LDF and OTO methods estimated fluctuations of saturation level and oxygen transport in microvasculature of periodontal tissues. With LFD identified changes in the concentration of enzymes (nicotinamide, flavins, lipofuscin, porphyrins) involved in metabolic processes Conclusion. Our preliminary results confirmed feasibility and safety the of intraoral ultrasound densitometry technique in the density of bone tissue of periodontium. Conclusion. Application of the diagnostic complex of above mentioned highly informative functional methods allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment.Keywords: electromyography (EMG), reodentography (RDG), laser Doppler flowmetry (LDF), reoperiodontography method (RPG), vital computer capillaroscopy (VCC), optical tissue oximetry (OTO), laser fluorescence diagnosis (LFD)
Procedia PDF Downloads 2802057 An Organocatalytic Construction of Vicinal Tetrasubstituted Stereocenters via Mannich Reaction of 2-Substituted Benzofuran-3-One with Isatin-Derived Ketimine
Authors: Koilpitchai Sivamuthuraman, Venkitasamy Kesavan
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3-substituted 3-amino-2-oxindole skeleton bearing adjacent tetrasubstituted stereogenic centers is of great importance because of these heterocyclic motifs possess a wide range of pharmacological activity. The catalytic asymmetric construction of multi functionalised heterocyclic compound with adjacent tetrasubstituted stereocenters is one of the most difficult tasks in organic synthesis. To date, the most straightforward methodologies have been developed for synthesis of chiral 3-substituted 3-amino-2-oxindoles through the addition of carbon nucleophiles to isatin-derived ketimines. However, only a few successful examples have been described for the assembly of vicinal tetrasubstituted stereocenters using isatin derived ketimines as electrophiles. On the other hand, 2,2-Disubstituted benzofuran-3(2H)-ones and related frameworks are characteristic of a quaternary stereogenic center at C2 position present in quite a number of natural products and bioactive Molecules.Despite the intensive efforts devoted for the construction of 2,2-Disubstituted Benzofuran-3[2H]-one, there are only a few asymmetric methods such as organocatalytic Michael addition and enantioselective halogenations were reported till now. Due to the biological importance of oxindole and benzofuran-3-one, it is proposed here with the synthesis of hybrid molecule containing tetrasubstituted stereo centers through asymmetric organocatalysis. The addition of 2-substituted Benzofuran-3-one(1a) to isatin-derived ketimines(2a) using a bifunctional organocatalyst(catalyst IV or V), leading to chiral heterocyclic compounds containing both 3-amino 2-oxindole and benzofurn-3-one bearing vicinal quaternary stereocenters with good yields and excellent enantioselectivity. The present study extends the scope of the catalytic asymmetric Mannich reaction with isatin-derived ketimines, providing a new class of amino oxindole derivatives having benzofuran-3-one.Keywords: asymmetric synthesis, benzofuran-3-one, isatin-derived ketimines, quaternary stereocenters
Procedia PDF Downloads 1912056 The Ameliorative Effects of the Histamine H3 Receptor Antagonist/Inverse Agonist DL77 on MK801-Induced Memory Deficits in Rats
Authors: B. Sadek, N. Khan, Shreesh K. Ojha, Adel Sadeq, D. Lazewska, K. Kiec-Kononowicz
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The involvement of Histamine H3 receptors (H3Rs) in memory and the potential role of H3R antagonists in pharmacological control of neurodegenerative disorders, e.g., Alzheimer disease (AD) is well established. Therefore, the memory-enhancing effects of the H3R antagonist DL77 on MK801-induced cognitive deficits were evaluated in passive avoidance paradigm (PAP) and novel object recognition (NOR) tasks in adult male rats, applying donepezil (DOZ) as a reference drug. Animals pretreated with acute systemic administration of DL77 (2.5, 5, and 10 mg/kg, i.p.) were significantly ameliorated in regard to MK801-induced memory deficits in PAP. The ameliorative effect of most effective dose of DL77 (5 mg/kg, i.p.) was abrogated when animals were pretreated with a co-injection with the H3R agonist R-(α)-methylhistamine (RAMH, 10 mg/kg, i.p.). Moreover, and in the NOR paradigm, DL77 (5 mg/kg, i.p.) reversed MK801-induced deficits long-term memory (LTM), and the DL77-provided procognitive effect was comparable to that of reference drug DOZ, and was reversed when animals were co-injected with RAMH (10 mg/kg, i.p.). However, DL77(5 mg/kg, i.p.) failed to alter short-term memory (STM) impairment in NOR test. Furthermore, DL77 (5 mg/kg) failed to induce any alterations of anxiety and locomotor behaviors of animals naive to elevated-plus maze (EPM), indicating that the ameliorative effects observed in PAP or NOR tests were not associated to alterations in emotions or in natural locomotion of tested animals. These results reveal the potential contribution of H3Rs in modulating CNS neurotransmission systems associated with neurodegenerative disorders, e.g., AD.Keywords: histamine H3 receptor, antagonist, learning and memory, Alzheimer's disease, neurodegeneration, passive avoidance paradigm, novel object recognition, behavioral research
Procedia PDF Downloads 1552055 Parameters Identification and Sensitivity Study for Abrasive WaterJet Milling Model
Authors: Didier Auroux, Vladimir Groza
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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization
Procedia PDF Downloads 3162054 Requests and Responses to Requests in Jordanian Arabic
Authors: Raghad Abu Salma, Beatrice Szczepek Reed
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Politeness is one of the most researched areas in pragmatics as it is key to interpersonal interactional phenomena. Many studies, particularly in linguistics, have focused on developing politeness theories and exploring linguistic devices used in communication to construct and establish social norms. However, the question of what constitutes polite language remains a point of ongoing debate. Prior research primarily examined politeness in English and its native speaking communities, oversimplifying the notion of politeness and associating it with surface-level language use. There is also a dearth of literature on politeness in Arabic, particularly in the context of Jordanian Arabic. Prior research investigating politeness in Arabic make generalized claims about politeness in Arabic without taking the linguistic variations into account or providing empirical evidence. This proposed research aims to explore how Jordanian Arabic influences its first language users in making and responding to requests, exploring participants' perceptions of politeness and the linguistic choices they make in their interactions. The study focuses on Jordanian expats living in London, UK providing an intercultural perspective that prior research does not consider. This study employs a mixed-methods approach combining discourse completion tasks (DCTs) with semi-structured interviews. While DCTs provide insight into participants’ linguistic choices, semi-structured interviews glean insight into participants' perceptions of politeness and their linguistic choices impacted by cultural norms and diverse experiences. This paper discusses previous research on politeness in Arabic, identifies research gaps, and discusses different methods for data collection. This paper also presents preliminary findings from the ongoing study.Keywords: politeness, pragmatics, jordanian arabic, intercultural politeness
Procedia PDF Downloads 792053 The Potential in the Use of Building Information Modelling and Life-Cycle Assessment for Retrofitting Buildings: A Study Based on Interviews with Experts in Both Fields
Authors: Alex Gonzalez Caceres, Jan Karlshøj, Tor Arvid Vik
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Life cycle of residential buildings are expected to be several decades, 40% of European residential buildings have inefficient energy conservation measure. The existing building represents 20-40% of the energy use and the CO₂ emission. Since net zero energy buildings are a short-term goal, (should be achieved by EU countries after 2020), is necessary to plan the next logical step, which is to prepare the existing outdated stack of building to retrofit them into an energy efficiency buildings. In order to accomplish this, two specialize and widespread tool can be used Building Information Modelling (BIM) and life-cycle assessment (LCA). BIM and LCA are tools used by a variety of disciplines; both are able to represent and analyze the constructions in different stages. The combination of these technologies could improve greatly the retrofitting techniques. The incorporation of the carbon footprint, introducing a single database source for different material analysis. To this is added the possibility of considering different analysis approaches such as costs and energy saving. Is expected with these measures, enrich the decision-making. The methodology is based on two main activities; the first task involved the collection of data this is accomplished by literature review and interview with experts in the retrofitting field and BIM technologies. The results of this task are presented as an evaluation checklist of BIM ability to manage data and improve decision-making in retrofitting projects. The last activity involves an evaluation using the results of the previous tasks, to check how far the IFC format can support the requirements by each specialist, and its uses by third party software. The result indicates that BIM/LCA have a great potential to improve the retrofitting process in existing buildings, but some modification must be done in order to meet the requirements of the specialists for both, retrofitting and LCA evaluators.Keywords: retrofitting, BIM, LCA, energy efficiency
Procedia PDF Downloads 2202052 Theoretical Modelling of Molecular Mechanisms in Stimuli-Responsive Polymers
Authors: Catherine Vasnetsov, Victor Vasnetsov
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Context: Thermo-responsive polymers are materials that undergo significant changes in their physical properties in response to temperature changes. These polymers have gained significant attention in research due to their potential applications in various industries and medicine. However, the molecular mechanisms underlying their behavior are not well understood, particularly in relation to cosolvency, which is crucial for practical applications. Research Aim: This study aimed to theoretically investigate the phenomenon of cosolvency in long-chain polymers using the Flory-Huggins statistical-mechanical framework. The main objective was to understand the interactions between the polymer, solvent, and cosolvent under different conditions. Methodology: The research employed a combination of Monte Carlo computer simulations and advanced machine-learning methods. The Flory-Huggins mean field theory was used as the basis for the simulations. Spinodal graphs and ternary plots were utilized to develop an initial computer model for predicting polymer behavior. Molecular dynamic simulations were conducted to mimic real-life polymer systems. Machine learning techniques were incorporated to enhance the accuracy and reliability of the simulations. Findings: The simulations revealed that the addition of very low or very high volumes of cosolvent molecules resulted in smaller radii of gyration for the polymer, indicating poor miscibility. However, intermediate volume fractions of cosolvent led to higher radii of gyration, suggesting improved miscibility. These findings provide a possible microscopic explanation for the cosolvency phenomenon in polymer systems. Theoretical Importance: This research contributes to a better understanding of the behavior of thermo-responsive polymers and the role of cosolvency. The findings provide insights into the molecular mechanisms underlying cosolvency and offer specific predictions for future experimental investigations. The study also presents a more rigorous analysis of the Flory-Huggins free energy theory in the context of polymer systems. Data Collection and Analysis Procedures: The data for this study was collected through Monte Carlo computer simulations and molecular dynamic simulations. The interactions between the polymer, solvent, and cosolvent were analyzed using the Flory-Huggins mean field theory. Machine learning techniques were employed to enhance the accuracy of the simulations. The collected data was then analyzed to determine the impact of cosolvent volume fractions on the radii of gyration of the polymer. Question Addressed: The research addressed the question of how cosolvency affects the behavior of long-chain polymers. Specifically, the study aimed to investigate the interactions between the polymer, solvent, and cosolvent under different volume fractions and understand the resulting changes in the radii of gyration. Conclusion: In conclusion, this study utilized theoretical modeling and computer simulations to investigate the phenomenon of cosolvency in long-chain polymers. The findings suggest that moderate cosolvent volume fractions can lead to improved miscibility, as indicated by higher radii of gyration. These insights contribute to a better understanding of the molecular mechanisms underlying cosolvency in polymer systems and provide predictions for future experimental studies. The research also enhances the theoretical analysis of the Flory-Huggins free energy theory.Keywords: molecular modelling, flory-huggins, cosolvency, stimuli-responsive polymers
Procedia PDF Downloads 702051 Induced Affectivity and Impact on Creativity: Personal Growth and Perceived Adjustment when Narrating an Intense Emotional Experience
Authors: S. Da Costa, D. Páez, F. Sánchez
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We examine the causal role of positive affect on creativity, the association of creativity or innovation in the ideation phase with functional emotional regulation, successful adjustment to stress and dispositional emotional creativity, as well as the predictive role of creativity for positive emotions and social adjustment. The study examines the effects of modification of positive affect on creativity. Participants write three poems, narrate an infatuation episode, answer a scale of personal growth after this episode and perform a creativity task, answer a flow scale after creativity task and fill a dispositional emotional creativity scale. High and low positive effect was induced by asking subjects to write three poems about high and low positive connotation stimuli. In a neutral condition, tasks were performed without previous affect induction. Subjects on the condition of high positive affect report more positive and less negative emotions, more personal growth (effect size r = .24) and their last poem was rated as more original by judges (effect size r = .33). Mediational analysis showed that positive emotions explain the influence of the manipulation on personal growth - positive affect correlates r = .33 to personal growth. The emotional creativity scale correlated to creativity scores of the creative task (r = .14), to the creativity of the narration of the infatuation episode (r = .21). Emotional creativity was also associated, during performing the creativity task, with flow (r = .27) and with affect balance (r = .26). The mediational analysis showed that emotional creativity predicts flow through positive affect. Results suggest that innovation in the phase of ideation is associated with a positive affect balance and satisfactory performance, as well as dispositional emotional creativity is adaptive.Keywords: affectivity, creativity, induction, innovation, psychological factors
Procedia PDF Downloads 1102050 Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data
Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L. Duan
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The conditional density characterizes the distribution of a response variable y given other predictor x and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts as a motivating starting point. In this work, the authors extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zₚ, zₙ]. The zₚ component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zₙ component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach coined Augmented Posterior CDE (AP-CDE) only requires a simple modification of the common normalizing flow framework while significantly improving the interpretation of the latent component since zₚ represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of 𝑥-related variations due to factors such as lighting condition and subject id from the other random variations. Further, the experiments show that an unconditional NF neural network based on an unsupervised model of z, such as a Gaussian mixture, fails to generate interpretable results.Keywords: conditional density estimation, image generation, normalizing flow, supervised dimension reduction
Procedia PDF Downloads 962049 Increased Reaction and Movement Times When Text Messaging during Simulated Driving
Authors: Adriana M. Duquette, Derek P. Bornath
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Reaction Time (RT) and Movement Time (MT) are important components of everyday life that have an effect on the way in which we move about our environment. These measures become even more crucial when an event can be caused (or avoided) in a fraction of a second, such as the RT and MT required while driving. The purpose of this study was to develop a more simple method of testing RT and MT during simulated driving with or without text messaging, in a university-aged population (n = 170). In the control condition, a randomly-delayed red light stimulus flashed on a computer interface after the participant began pressing the ‘gas’ pedal on a foot switch mat. Simple RT was defined as the time between the presentation of the light stimulus and the initiation of lifting the foot from the switch mat ‘gas’ pedal; while MT was defined as the time after the initiation of lifting the foot, to the initiation of depressing the switch mat ‘brake’ pedal. In the texting condition, upon pressing the ‘gas’ pedal, a ‘text message’ appeared on the computer interface in a dialog box that the participant typed on their cell phone while waiting for the light stimulus to turn red. In both conditions, the sequence was repeated 10 times, and an average RT (seconds) and average MT (seconds) were recorded. Condition significantly (p = .000) impacted overall RTs, as the texting condition (0.47 s) took longer than the no-texting (control) condition (0.34 s). Longer MTs were also recorded during the texting condition (0.28 s) than in the control condition (0.23 s), p = .001. Overall increases in Response Time (RT + MT) of 189 ms during the texting condition would equate to an additional 4.2 meters (to react to the stimulus and begin braking) if the participant had been driving an automobile at 80 km per hour. In conclusion, increasing task complexity due to the dual-task demand of text messaging during simulated driving caused significant increases in RT (41%), MT (23%) and Response Time (34%), thus further strengthening the mounting evidence against text messaging while driving.Keywords: simulated driving, text messaging, reaction time, movement time
Procedia PDF Downloads 5232048 Learning Aid for Kids in India
Authors: Prabir Mukhopadhyay, Atul Kohale
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Going to school for Indian kids is a panic situation. Many of them are unable to adjust themselves to the confinement of the school building and this problem is compounded by other factors like unknown people in the vicinity, absence of either parents etc. This project aims at addressing these issues by exposing the kids at home to the learning environment. The purpose is to design a physical model with interfaces at each surface. The model would be like a cube with interactive surfaces where the child would be able to draw, paint, complete a picture and do such fun activities.Keywords: interface, kids, play, computer systems engineering
Procedia PDF Downloads 2132047 Marker-Controlled Level-Set for Segmenting Breast Tumor from Thermal Images
Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy
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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms
Procedia PDF Downloads 3802046 Optimizing Parallel Computing Systems: A Java-Based Approach to Modeling and Performance Analysis
Authors: Maher Ali Rusho, Sudipta Halder
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The purpose of the study is to develop optimal solutions for models of parallel computing systems using the Java language. During the study, programmes were written for the examined models of parallel computing systems. The result of the parallel sorting code is the output of a sorted array of random numbers. When processing data in parallel, the time spent on processing and the first elements of the list of squared numbers are displayed. When processing requests asynchronously, processing completion messages are displayed for each task with a slight delay. The main results include the development of optimisation methods for algorithms and processes, such as the division of tasks into subtasks, the use of non-blocking algorithms, effective memory management, and load balancing, as well as the construction of diagrams and comparison of these methods by characteristics, including descriptions, implementation examples, and advantages. In addition, various specialised libraries were analysed to improve the performance and scalability of the models. The results of the work performed showed a substantial improvement in response time, bandwidth, and resource efficiency in parallel computing systems. Scalability and load analysis assessments were conducted, demonstrating how the system responds to an increase in data volume or the number of threads. Profiling tools were used to analyse performance in detail and identify bottlenecks in models, which improved the architecture and implementation of parallel computing systems. The obtained results emphasise the importance of choosing the right methods and tools for optimising parallel computing systems, which can substantially improve their performance and efficiency.Keywords: algorithm optimisation, memory management, load balancing, performance profiling, asynchronous programming.
Procedia PDF Downloads 122045 Violence against Police Officers in Germany
Authors: Anne T. Herr, Clemens Lorei
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Employees of organizations with security tasks, such as emergency services, public order services, or police forces, work every day to ensure people's safety. Violence against police is, therefore, a relevant topic both socially and politically. An increase in violence is often discussed without there being any verifiable and generally valid data. So far, scientific research has mainly focused on offender characteristics and crime statistics. These surveys are mostly subjective, retrospective, and neglect the dynamics and interactions in concrete violent situations. Therefore, more recent research methods attempt to capture the issue of violence against emergency forces more comprehensively. However, the operationalization of the constructs and the methodological approach pose particular challenges. This contribution provides an overview of new perspectives on the understanding of violent assaults and identifies current research gaps. In addition, a new research project of the Hessian University of Police and Administration in Germany is presented. In the 'AMBOSafe' study, different theoretical backgrounds for understanding violence against police and emergency services personnel will be combined in order to capture as many different perspectives of violent assaults as possible in a multimodal research approach. In a retrospective as well as in a longitudinal survey, the conditions of escalation dynamics in the assaults are recorded and supplemented by the current and valid prevalence of physical and verbal assaults in a period of four months. In addition, qualitative interviews with those affected will be used to record more detailed descriptions of and the feelings during the assaults, as well as possible causes and connections between the different groups of people. In addition to the reports of the police forces, the motives of the attackers will be collected and supplemented by analyzing the criminal case files. This knowledge can contribute to a more comprehensive understanding of violent assaults against police forces in order to be able to derive scientifically based preventive measures.Keywords: assaults, crime statistics, escalation dynamics, police
Procedia PDF Downloads 1142044 Control and Automation of Sensors in Metering System of Fluid
Authors: Abdelkader Harrouz, Omar Harrouz, Ali Benatiallah
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This paper is to present the essential definitions, roles and characteristics of automation of metering system. We discuss measurement, data acquisition and metrological control of a signal sensor from dynamic metering system. After that, we present control of instruments of metering system of fluid with more detailed discussions to the reference standards.Keywords: communication, metering, computer, sensor
Procedia PDF Downloads 5552043 Depression among University Students an Epidemiological Study on a Sample of University Students
Authors: Laid Fekih
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Background: Depression affects people in all communities across the world and in all aspects of their lives. Its spread varies from one country to another, can happen at any age and get rid of it is not easy. There is no clear policy in Algeria's higher education institutions to detect and treat these disorders or pay particular attention to those at risk. Identifying the prevalence of depression among Algerian students, its correlation with different variables, and studying gender differences in the light of a range of variables is necessary to develop an appropriate plan to raise the level of hope and love of life among students. Method: Random samples of 1500 University of Tlemcen students (967 girls and 533 boys), aged 19 to 24 years completed a self-administered questionnaire that included Beck's Depression Inventory ®-II (BDI®-II), (School Health Promotion: The Mood part), Other questions included in this survey focused on demographic characteristics including gender, age and year of study, academic performance (Annual Average Score (0-20) AAS), were examined. Results: The rate of depression (moderate, severe and extreme) varied from 03% to 13% among university students in Tlemcen University. There was no difference in the rates of depression in male and female students, which means that male and female students do have similar rates of depression. The rate of depression in the first-year of the study shows a higher score relative to students of other years. Depression has a negative relationship with academic performance, which means that depressed students have many difficulties in academic tasks at university. Conclusion: Depression among university students is an important center of interest in the world, not only because of the ease with which they can be followed, or the difficulties encountered during their studies and their technical courses but for the link between the level of depression and the quality of care of mental health services, especially if many students with mood and emotional problems don't meet the criteria for psychotherapy.Keywords: depression, epidemiology, university students, academic performance
Procedia PDF Downloads 1442042 Action Research: The Goal Setting Intervention Promotes Students' Academic Achievement of the Bachelors of Early Childhood Education Program During the COVID-19 Pandemic
Authors: Mashaal Hooda
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The rationale for conducting this action research was to increase students' Academic Achievement (AA) contexts of studying/researching by employing the Goal Setting intervention (GS). The purposive sample consisted of 10 female undergraduate students at a university in Dubai. The intervention was introduced through workshop classes conducted online. The pre-intervention consisted of discussions concentrating on participants' research contexts amidst a pandemic. The GS moderators were implemented in the class, followed by scaffolding and mentoring interactions and self-reflective accounts of students' actions and feelings of using the intervention to better plan and structure their dissertation tasks. The research incorporated a Mixed Methods Methodology (MMM). Quantitative data collection took place through surveys, while qualitative data were collected using semi-structured interviews. Triangulation of the emergent themes showed a positive increase in students achievable GS, self-regulatory study skills, feedback-seeking behaviours, research organisation and synthesis, self-reflection and Academic Resilient (AR) attitudes amalgamate to enhance students' AA outcomes. Though, students' intrinsic motivational levels to study and research observed minor changes only. Nonetheless, the pebble in the shoe was removed as students AA contexts improved in undertaking better actionable steps for their research. Therefore, the GS intervention enabled students to set, balance, and achieve academic goals while catering to their academic anxieties, mental health concerns, and adaptability to the e-learning platforms amidst the COVID-19 pandemic. Despite the wide-scale changes the pandemic brought to the teaching and learning communities, the GS intervention served as a targeted intervention to help students maintain their achievement contexts in a goal-oriented way.Keywords: academic achievement, acadeic resilience, COVID-19, goal setting
Procedia PDF Downloads 1442041 Review of the Road Crash Data Availability in Iraq
Authors: Abeer K. Jameel, Harry Evdorides
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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.Keywords: road safety, Iraq, crash data, road risk assessment, The International Road Assessment Program (iRAP)
Procedia PDF Downloads 2562040 Turin, from Factory City to Talents Power Player: The Role of Private Philanthropy Agents of Innovation in the Revolution of Human Capital Market in the Contemporary Socio-Urban Scenario
Authors: Renato Roda
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With the emergence of the so-called 'Knowledge Society', the implementation of policies to attract, grow and retain talents, in an academic context as well, has become critical –both in the perspective of didactics and research and as far as administration and institutional management are concerned. At the same time, the contemporary philanthropic entities/organizations, which are evolving from traditional types of social support towards new styles of aid, envisaged to go beyond mere monetary donations, face the challenge of brand-new forms of complexity in supporting such specific dynamics of the global human capital market. In this sense, it becomes unavoidable for the philanthropic foundation, while carrying out their daily charitable tasks, to resort to innovative ways to facilitate the acquisition and the promotion of talents by academic and research institutions. In order to deepen such a specific perspective, this paper features the case of Turin, former 'factory city' of Italy’s North West, headquarters -and main reference territory- of Italy’s largest and richest private formerly bank-based philanthropic foundation, the Fondazione Compagnia di San Paolo. While it was assessed and classified as 'medium' in the city Global Talent Competitiveness Index (GTCI) of 2020, Turin has nevertheless acquired over the past months status of impact laboratory for a whole series of innovation strategies in the competition for the acquisition of excellence human capital. Leading actors of this new city vision are the foundations with their specifically adjusted financial engagement and a consistent role of stimulus towards innovation for research and education institutions.Keywords: human capital, post-Fordism, private foundation, war on talents
Procedia PDF Downloads 1712039 Teaching Practices for Subverting Significant Retentive Learner Errors in Arithmetic
Authors: Michael Lousis
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The systematic identification of the most conspicuous and significant errors made by learners during three-years of testing of their progress in learning Arithmetic throughout the development of the Kassel Project in England and Greece was accomplished. How much retentive these errors were over three-years in the officially provided school instruction of Arithmetic in these countries has also been shown. The learners’ errors in Arithmetic stemmed from a sample, which was comprised of two hundred (200) English students and one hundred and fifty (150) Greek students. The sample was purposefully selected according to the students’ participation in each testing session in the development of the three-year project, in both domains simultaneously in Arithmetic and Algebra. Specific teaching practices have been invented and are presented in this study for subverting these learners’ errors, which were found out to be retentive to the level of the nationally provided mathematical education of each country. The invention and the development of these proposed teaching practices were founded on the rationality of the theoretical accounts concerning the explanation, prediction and control of the errors, on the conceptual metaphor and on an analysis, which tried to identify the required cognitive components and skills of the specific tasks, in terms of Psychology and Cognitive Science as applied to information-processing. The aim of the implementation of these instructional practices is not only the subversion of these errors but the achievement of the mathematical competence, as this was defined to be constituted of three elements: appropriate representations - appropriate meaning - appropriately developed schemata. However, praxis is of paramount importance, because there is no independent of science ‘real-truth’ and because praxis serves as quality control when it takes the form of a cognitive method.Keywords: arithmetic, cognitive science, cognitive psychology, information-processing paradigm, Kassel project, level of the nationally provided mathematical education, praxis, remedial mathematical teaching practices, retentiveness of errors
Procedia PDF Downloads 3162038 Lexical Based Method for Opinion Detection on Tripadvisor Collection
Authors: Faiza Belbachir, Thibault Schienhinski
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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score
Procedia PDF Downloads 1982037 Modeling of Glycine Transporters in Mammalian Using the Probability Approach
Authors: K. S. Zaytsev, Y. R. Nartsissov
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Glycine is one of the key inhibitory neurotransmitters in Central nervous system (CNS) meanwhile glycinergic transmission is highly dependable on its appropriate reuptake from synaptic cleft. Glycine transporters (GlyT) of types 1 and 2 are the enzymes providing glycine transport back to neuronal and glial cells along with Na⁺ and Cl⁻ co-transport. The distribution and stoichiometry of GlyT1 and GlyT2 differ in details, and GlyT2 is more interesting for the research as it reuptakes glycine to neuron cells, whereas GlyT1 is located in glial cells. In the process of GlyT2 activity, the translocation of the amino acid is accompanied with binding of both one chloride and three sodium ions consequently (two sodium ions for GlyT1). In the present study, we developed a computer simulator of GlyT2 and GlyT1 activity based on known experimental data for quantitative estimation of membrane glycine transport. The trait of a single protein functioning was described using the probability approach where each enzyme state was considered separately. Created scheme of transporter functioning realized as a consequence of elemental steps allowed to take into account each event of substrate association and dissociation. Computer experiments using up-to-date kinetic parameters allowed receiving the number of translocated glycine molecules, Na⁺ and Cl⁻ ions per time period. Flexibility of developed software makes it possible to evaluate glycine reuptake pattern in time under different internal characteristics of enzyme conformational transitions. We investigated the behavior of the system in a wide range of equilibrium constant (from 0.2 to 100), which is not determined experimentally. The significant influence of equilibrium constant in the range from 0.2 to 10 on the glycine transfer process is shown. The environmental conditions such as ion and glycine concentrations are decisive if the values of the constant are outside the specified range.Keywords: glycine, inhibitory neurotransmitters, probability approach, single protein functioning
Procedia PDF Downloads 1192036 Lightweight and Seamless Distributed Scheme for the Smart Home
Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro
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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.Keywords: authentication, key-session, security, wireless sensors
Procedia PDF Downloads 3182035 Lifestyle Behaviors among Jordanian Obese Children Aged 6-9 Years: A Cross-Sectional Study
Authors: Ayman Bani Salameh
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Background: Obesity in children is in increasing in developed and developing countries, which leads to morbidity and premature mortality. Lifestyle behaviors are an important issue in minimizing this problem and subsequent complications. Thus, this study purposed to assess lifestyle behaviors, including dietary habits and physical activity, among Jordanian obese children aged 6-9 years. Methods: A cross-sectional study was conducted on 324 children aged 6-9 years using a questionnaire consisting of items measuring dietary habits (7 items) and physical activity (8 items). Results: Findings showed that obese children had bad dietary habits involved in the number of meals eaten day (M= 5.06, SD=1.14), number of snacks of sweet/ chocolates daily (M= 3. 61, SD=0.82), and number of glasses of sweet fizzy drinks/day (M= 3.39, SD=0.96). Moreover, they had poor physical activity represented in the number of playing or training in an activity like dancing, swimming, and walking in the past week (M= 0.06, SD=1.01), number of days in participating in moderate physical activity last week (M= 0.06, SD=1.01), time spending in using a computer, watching TV, watching videos or using the internet as a part of study or homework in the last week (M= 16.88, SD=2.37), and ), time spending in using a computer, watching TV, watching videos or using the internet for fun or recreation in the past week (M= 14.44, SD=2.37). Conclusion: Obese children aged 6-9 had unhealthy lifestyle behaviors, which could expose them to a high risk of increasing comorbidities associated with obesity. Therefore, this preliminary study helps develop an intervention program based on modifying unhealthy behaviors, including bad dietary habits and a sedentary lifestyle. The results provide baseline data about the strategies for developing intervention programs for weight reduction.Keywords: obesity, children, behaviors, lifestyle
Procedia PDF Downloads 832034 Improving Home and School Collaboration: Analysis of Parent and Teacher Involvement Practices in Public Elementary Schools in Benguet, Philippines
Authors: Sherry Junette Tagle
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Extensive research continues to prove the positive effects of home and school collaborations in education. Although parent involvement programs in Benguet, Philippines are in place, the impact has yet to affect the current aggregate performance of elementary pupils. This study describes the involvement of public elementary teachers and parents along Epstein’s types of involvement using the sequential explanatory design. Survey and interview results show that teachers place greater value on activities that cater to communicating, volunteering, learning at home and decision making. On the other hand, parents are actively involved in all six types and value the importance of their involvement in school to their child’s schooling. Parents of grades 1-4 pupils significantly give importance to communicating activities to offset difficulties encountered by young pupils while parents of grades 5-6 pupils, have declining interest in volunteering and learning at home activities citing older children as being more independent to do teacher-assigned tasks. Teachers, compared to the other respondent groups, significantly place higher value on the importance of parent leaders as their partners in implementing school activities. In general, involvement of parents and teachers in home-school activities is intensive in the lower grade levels and decreases as their child progresses through school. A recommended program for future collaborations of the Philippine’s Department of Education has been formulated to diversify existing activities and elicit greater participation among the school’s stakeholders to achieve holistic development of the pupils and ultimately improve pupils’ school aggregate performance.Keywords: Epstein's types of involvement, community collaborations, home and school partnerships, parent involvement
Procedia PDF Downloads 248