An Overview on Evaluation of E-Learning/Training Response Time Considering Artificial Neural Networks Modeling

The objective of this piece of research is to interpret and investigate systematically an observed brain functional phenomenon which associated with proceeding of e-learning processes. More specifically, this work addresses an interesting and challenging educational issue concerned with dynamical evaluation of e-learning performance considering convergence (response) time. That's based on an interdisciplinary recent approach named as Artificial Neural Networks (ANNs) modeling. Which incorporate Nero-physiology, educational psychology, cognitive, and learning sciences. Herein, adopted application of neural modeling results in realistic dynamical measurements of e-learners' response time performance parameter. Initially, it considers time evolution of learners' experienced acquired intelligence level during proceeding of learning / training process. In the context of neurobiological details, the state of synaptic connectivity pattern (weight vector) inside e-learner's brain-at any time instant-supposed to be presented as timely varying dependent parameter. The varying modified synaptic state expected to lead to obtain stored experience spontaneously as learner's output (answer). Obviously, obtained responsive learner's output is a resulting action to any arbitrary external input stimulus (question). So, as the initial brain state of synaptic connectivity pattern (vector) considered as pre-intelligence level measured parameter. Actually, obtained e-learner’s answer is compatibly consistent with modified state of internal / stored experienced level of intelligence. In other words, dynamical changes of brain synaptic pattern (weight vector) modify adaptively convergence time of learning processes, so as to reach desired answer. Additionally, introduced research work is motivated by some obtained results for performance evaluation of some neural system models concerned with convergence time of learning process. Moreover, this paper considers interpretation of interrelations among some other interesting results obtained by a set of previously published educational models. The interpretational evaluation and analysis for introduced models results in some applicable studies at educational field as well as medically promising treatment of learning disabilities. Finally, an interesting comparative analogy between performances of ANNs modeling versus Ant Colony System (ACS) optimization presented at the end of this paper

Geometrical Dynamics by the Schrödinger Equation and Coherent States Transform

This thesis is concerned with a concept of geometrising time evolution of quantum systems. This concept is inspired by the fact that the Legendre transform expresses dynamics of a classical system through first-order Hamiltonian equations. We consider, in this thesis, coherent state transforms with a similar effect in quantum mechanics: they reduce certain quantum Hamiltonians to first-order partial differential operators. Therefore, the respective dynamics can be explicitly solved through a flow of points in extensions of the phase space. This, in particular, generalises the geometric dynamics of a harmonic oscillator in the Fock-Segal-Bargmann (FSB) space. We describe all Hamiltonians which are geometrised (in the above sense) by Gaussian and Airy beams and exhibit explicit solutions for such system

Numerical solution for the time-Fractional Diffusion-wave Equations by using Sinc-Legendre Collocation Method

In this paper the numerical solution of fractional diffusion wave equation is proposed. The fractional derivative will be in the Caputo sense. The proposed method will be based on shifted Legendre collocation scheme and sinc function approximation for time and space respectively. The problem is reduced to the problem into a system of algebraic equations after implementing this method. For demonstrating the validity and applicability of the proposed numerical scheme some examples are presented. Keywords: Fractional diffusion equation, Sinc functions, shifted Legendre  polynomials, Collocation method

Importance of marine prey to growth of estuarine tern chicks: evidence from an energetic balance model

We assessed the effects of quality and quantity of prey species on the growth of Little Tern Sterna albifrons chicks raised in salinas (salt-pans), Algarve, Portugal. An energetic balance model was developed, which estimated the total amount of energy ingested by all chicks in a nest and the energy expenditure by the chicks when either growing alone or in groups of two and three per nest. Energy intake per chick depended on the energy available per nest and a competition value for food between chicks. Energy expenditure was defined by the basal metabolic rate (BMR), which depends on chick\u2019s weight, plus a multiple of BMR, obtained by calibration and accounting for unspecified energetic losses. Prey species ingested by Little Tern chicks were mainly the fishes sand- smelt Atherina spp., Sardine Sardina pilchardus, Garfish Belone belone and mummichog Fundulus spp., but also two types of shrimp (Paleo- monetes spp. and Paleomon spp.). Although prey species more abundant in salinas (shrimps and Fundulus spp.) were delivered at a higher rate, and Fundulus spp. had the greatest calorific content, chick growth was more sensitive to alterations in the ingestion of typically marine fish species, such as Sardina pilchardus and Belone belone. Model predictions were in agreement with data obtained in the field, as adults breeding in salinas foraged regularly at sea. Practical considerations from the pre- sent results are: (1) birds breeding in salinas rely on a sufficient amount of typically marine prey to ensure the growth of their chicks; (2) in some years foraging conditions in the salinas can be favourable, appar- ently because high food abundance (plus proximity to nests) may com- pensate for relatively poor quality of food types encounteredFCT Project POCTI/BSE/37385/200

Synthesis and Study of the Antimicrobial Activity of Modified Polyvinyl Alcohol Films Incorporated with Silver Nanoparticles

       A new class of biologically active nanocomposites and modified polymers based on poly (vinyl alcohol) (PVA) with some organic compounds [II, IV, V and VI] were synthesized using silver nanoparticles (Ag-NPs). All compounds were synthesized using nucleophilic substitution interactions and characterized by FTIR, DSC and TGA. The biological activity of the modified polymers was evaluated against: gram (+) (staphylococcus aureus) and gram (-): (Es cherichia coli bacteria). Antimicrobial films are developed based on modified poly (vinyl alcohol) MPVA and Ag-NPs nanoparticles. The nanocomposites and modified polymers showed better antibacterial activities against Escherichia coli (Gram negative) than against Staphylococcus aureus (Gram positive). This work also studied the effect of using different amounts of nanoparticles on the effectiveness against bacteria and it was found that nanocomposite (P2/Ag 5%) has superior antibacterial properties against Escherichia coli

Design and implement WSN/IoT smart parking management system using microcontroller

With the dramatic expansion of new networks such as Wireless Sensor Network (WSN) and Internet-of-Things (IoT), tremendous opportunities have been emerged to incorporate such technologies for valuable tasks. One of these tasks is the smart car parking where there is an imperative demand to manage the parkings in various facilities which may help drivers to save their time. Several research studies have addressed this task using wide range of approaches. However, the energy consumption is still a serious concern. This paper proposes a smart car parking based on cloud-based approach along with variety of sensors. Passive Infrared Sensors (PIRs) have been used to sense the object motion. While Light Dependent Resistor (LDR) sensors have been utilized to sense the light of the parking alarm and display inmformation regarding the occupied and non-occupied parking lots. Finally, multi-micro controller of Arduino have been exploited in order to transmit the information collected to the server. Finally, a prototype Android application has been developed in order to recieve the infromation from the server. Results of simulation showed the efficacy of the proposed method

Does Speaker Age Affect Speech Perception in Noise in Older Adults?

Purpose: To investigate the effects of speaker age, speaker gender, semantic context, signal-to-noise ratio (SNR) and a listener’s hearing status on speech recognition and listening effort in older adults. We examined the hypothesis that older adults would recognize less speech and exert greater listening effort when listening to the speech of younger versus older adult speakers. Method: Speech stimuli were recorded from 12 adult speakers classified as “younger” (three males and three females aged 18-31 years) and “older” (three males and three females aged 69-89) respectively. A computer-based subjective rating was conducted to confirm that the speakers were representative of younger and older speakers. Listeners included 20 older adults (aged 65 years and above), who were divided into two age-matched groups with and without hearing loss. All listening and speaking participants in the study were native speakers of New Zealand English. A dual-task paradigm was used to measure speech recognition and listening effort; the primary task involved recognition of target words in sentences containing either high or low contextual cues, while the secondary task required listeners to memorise the target words for later recall, following a set number of sentences. Listening tasks were performed with a variety of listening conditions (quiet, +5 dB SNR and 0dB SNR). Results: There were no overall differences in speech recognition scores or word recall scores for the 20 older listeners, when listening to the speech of the younger versus older speakers. However, differential effects of speaker group were observed in the two semantic context conditions (high versus low context). Older male speakers were the easiest to understand when semantic context was low; however, for sentences with high semantic context, the older male group were the most difficult to understand. Word recall scores were also significantly higher in the most challenging listening condition (low semantic context, 0 dB SNR), when the speaker was an older male. Conclusion: Differential effects of speaker group were observed in the two semantic context conditions (high versus low context) suggesting that different speech cues were used by listeners, as the level of context varied. The findings provide further evidence that, in challenging listening conditions, older listeners are able to use a wide range of cues, such as prosodic features and semantic context to compensate for a degraded signal. The availability of these cues depends on characteristics of the speaker, such as rate of speech and prosody, as well as characteristics of the listener and the listening environment.

Epigenetics in Male Infertility

Male infertility is a complex medical condition, in which epigenetic factors play an important role. Epigenetics has recently gained significant scientific attention since it has added a new dimension to genomic and proteomic research. As a mechanism for maintaining genomic integrity and controlling gene expression, epigenetic modifications hold a great promise in capturing the subtle, yet very important, regulatory elements that might drive normal and abnormal sperm functions. The sperm’s epigenome is known to be marked by constant changing over spermatogenesis, which is highly susceptible to be influenced by a wide spectrum of environmental stimuli. Recently, epigenetic aberrations have been recognized as one of the causes of idiopathic male infertility. Recent advances in technology have enabled humans to study epigenetics role in male infertility