study aims to determine the effectiveness of brain-based learning strategies profile on the multiple intelligences of children living under stressful conditions in Gaza. A case control study was conducted with a purposive sample comprising 45 children (ages 12 to 15 years) in the experimental group and 48 children (ages 12 to 15 years) in the control group. The subjects in two groups were assessed for multiple intelligences before and after brain-based learning strategies profile intervention. No significant differences were found between the experimental and control groups in the pretest results, whereas the posttest results indicated significant differences in all domains excepted musical and intrapersonal intelligences. Brain-based learning strategies are effective and useful for linguistic, mathematical, spatial, kinesthetic, interpersonal and naturalist intelligences.
The Government of India is transcending from traditional modus operandi ofgovernance towards technological involvement in the process of governance.Currently, the Government of India is in the transition phase and seamlesslyunleashing the power of ICT in governance. The government is spending anenormous amount of finances in deployment of e-governance, but, are theseefforts are going in the appropriate direction and leads towards intendedresults? What do the people percept from the concept of e-governance? What isthe global perspective about perception of e-governance? What are the majorchallenges confronting the deployment of e-governance? In this attempt theauthors have made an attempt to riposte aforesaid issues. Moreover, the authorshave also suggested some plausible suggestions which may help in successful andsustainable deployment of e-governance in India.
a great advancement in science and technology, efficient techniques are needed for the purpose of security and copyright protection of the digital information being transmitted over the internet and for secret data communication. Thus, Steganography solves this purpose which has been used widely. Even though, a Stego-object may be exposed to noise or compression due to which the secret data cannot be extracted correctly at the receiver's end, when the transmission occours. This paper presents an efficient image hiding scheme, Social Impact theory based Optimization (SITO). Here, a fitness function is computed based on certain texture properties and entropy of a host image. According to this, the block holding the most relevant fitness value is the place where embedding of the secret data (secret image) is done. Thus, a stego-image is retrieved at the other end, which is not only good in quality but is also able to sustain certain noise and compression attacks during the transmission. The objective function is defined in such a manner that both quality and robustness of the stego image are acceptable, for which the performance analysis parameter values of the stego-image are also determined. The results, when compared with some other data hiding technique show better stego image quality along with distortion tolerance.
One of the current theoretically significant, simple and very effective texture descriptor that describe local structure efficiently and precisely is the ‘Local Binary Pattern’ (LBP). Today LBP and its variants are applied in many areas. One of the disadvantage with LBP is it derives a total of 256 patterns out of which 58 are the Uniform LBP (ULBP) and remaining are Non Uniform LBP (NULBP).The ULBP holds the fundamental characteristic and most of the textures predominantly contain ULBP . The disadvantage with ULBP is one should consider 58 pattern features for any classification or retrieval etc. The ULBP approaches completely ignored the NULBP and grouped them into mislenious class. This leads to lot of complexity. To overcome this, present paper designed a new method for retrieval based on histogram of transitions from 0 to 1 or 1 to 0 on LBP. LBP contains only 5 such transitions (0 or 2 or 4 or 6 or 8). The proposed method is experimented on various images collected from Google data base. The experimental result indicates the efficiency of the proposed method over the various methods.
In this letter, a technique for enhancement of bandwidth along with gain is proposed here. This article deals with design, modeling and simulation of slotted antenna. A star shaped parasitic patch is introduced in the centre of antenna to improve the gain along with the bandwidth by exciting additional resonances. For enhancing bandwidth, a slotted approach is used in ground of antenna along with rotation in patch and a simple 50 Ώ microstrip line fed is used to excite the slot in the antenna. Simulated results shows that a good amount of bandwidth (approx. 2.89 GHz) and gain (approx. 8.05 dB) is achieved ranging from 2.37 to 4.55 GHz using Ansoft HFSS software. The proposed antenna shows its application in WIMAX and WLAN bands along with comparative analysis between parasitic patch and without parasitic patch at the last.
Creating an accurate Speech Emotion Recognition (SER) system depends on extracting features relevant to that of emotions from speech. In this paper, the features that are extracted from the speech samples include Mel Frequency Cepstral Coefficients (MFCC), energy, pitch, spectral flux, spectral roll-off and spectral stationarity. In order to avoid the ‘curse of dimensionality’, statistical parameters, i.e. mean, variance, median, maximum, minimum, and index of dispersion have been applied on the extracted features. For classifying the emotion in an unknown test sample, Support Vector Machines (SVM) has been chosen due to its proven efficiency. Through experimentation on the chosen features, an average classification accuracy of 86.6% has been achieved using one-v/s-all multi-class SVM which is further improved to 100% when reduced to binary form problem. Classifier metrics viz. precision, recall, and F-score values show that the proposed system gives improved accuracy for Emo-DB.
In this paper an efficient method for parameter extraction of solar cell double diode model using Artificial Bee Colony (ABC) Algorithm is presented. ABC packs solid features such as simplicity of implementation, promising optimization capability, fewer control parameters, etc. In this paper we have implemented various methods suggested to boost traditional ABC performance to solve multiparameter optimization problem. The results demonstrate ability of modified algorithm to be primary candidate for the parameter extraction in wide search space.