A Research-Based Evidence of the Effect of Graphic Organizers on the Understanding of Prose Fiction in ESL Classroom

Graphic organizers (GOs) are fast becoming acceptable standard instructional tools across subjects in the education arena globally. However, this visual representation of information is yet to be recognized and integrated into the teaching methods in Nigerian schools. This study, therefore, presents a research-based investigation of the usefulness of GOs in the appreciation of prose literature in Nigeria, with a view to foregrounding their use in Nigerian schools. Specifically, the study seeks to find out whether senior secondary students in prose literature-in-English in Nigeria who are taught with GOs perform better in prose and comprehension assessments. Four project secondary schools with total of 100 students were purposively selected for the study. The schools were grouped into two: graphic-based schools (GBS) and non-graphic-based schools (NGBS). Whereas the GBS was exposed to instruction via eight graphic organizers, the NGBS served as control. Subjected to descriptive statistics and one-sample t test analysis, the investigation reveals that graphic organizers make students take charge of the learning process in prose literature classes, and it concludes that these visual instructional elements guarantee student understanding and achievement. The study, thus, recommends the incorporation of graphic organizers in the teaching and learning processes across subjects in Nigerian school

New Method of LMS Variable Step-Size Formulation for Adaptive Noise Cancellation

Least mean square (LMS) is a widely used steepest descent algorithm known with efficient tracking ability of small mean square error (MSE) but with low convergence speed. In contract to the fixed step size, variable step size was introduced to improve the convergence speed while maintaining the minimal MSE. In this work, a new method was formulated to determine the variable step size of the LMS algorithm. Simulation results are presented to support the experimental analysis for the performance evaluation and comparison. Result reveals that the performance the of new formulated variable step size algorithm is better compare to the conventional LMS algorithm

Cooperative-hybrid detection of primary user emulators in cognitive radio networks

Primary user emulator (PUE) attack occurs in Cognitive Radio Networks (CRNs) when a malicious secondary user (SU) poses as a primary user (PU) in order to deprive other legitimate SUs the right to free spectral access for opportunistic communication. In most cases, these legitimate SUs are unable to effectively detect PUEs because the quality of the signals received from a PUE may be severely attenuated by channel fading and/or shadowing. Consequently, in this paper, we have investigated the use of cooperative spectrum sensing (CSS) to improve PUE detection based on a hybrid localization scheme. We considered different pairs of secondary users (SUs) over different received signal strength (RSS) values to evaluate the energy efficiency, accuracy, and speed of the new cooperative scheme. Based on computer simulations, our findings suggest that a PUE can be effectively detected by a pair of SUs with a low Root Mean Square Error rate of 0.0047 even though these SUs may have close RSS values within the same cluster. Furthermore, our scheme performs better in terms of speed, accuracy and low energy consumption rates when compared with other PUE detection schemes. Thus, it is a viable proposition to better detect PUEs in CRNs

WOMEN IN POLITICS: THE NIGERIAN FACTOR

In a typical patriarchal African setting, women are usually relegated to the background. They are seen, not heard in a man’s world. In the religious circle, for instance, women are not expected to preside over men; they are not expected to be ordained as Priests, Pastors, etc. in most church denominations. Politics in Nigeria has always been a turbulent terrain. There is the usual male chauvinism that the male counterparts don’t yield an inch to the opposite sex. The general age-long belief and practice is that men must always lead and the position of the female invariably is in the kitchen. Could that be as a result of the fact that a woman was created out of a man, which smacks of superiority and inferiority syndrome, a weaker vessel as opposed to a stronger vessel? Undoubtedly, as a result of man’s dominance in the political space of our national life, in Nigeria, men have been able, for some-time, to garner economic power which they use to fight or bargain for political power. This paper identifies and focuses on prominent Nigerian women who have blazed the trail in spite of the hurdles placed on women’s way by the policies and structures of their male-counterparts. The objective of the study is to sensitize the women-folk on the need for leadership positions in the political arena. The main sources of data are the newspapers, journal articles, the internet, the library, interviews and questionnaires from the public

A real valued neural network based autoregressive energy detector for cognitive radio application

A real valued neural network (RVNN) based energy detector (ED) is proposed and analyzed for cognitive radio (CR) application. This was developed using a known two-layered RVNN model to estimate the model coefficients of an autoregressive (AR) system. By using appropriate modules and a well-designed detector, the power spectral density (PSD) of the AR system transfer function was estimated and subsequent receiver operating characteristic (ROC) curves of the detector generated and analyzed. A high detection performance with low false alarm rate was observed for varying signal to noise ratio (SNR), sample number, and model order conditions. The proposed RVNN based ED was then compared to the simple periodogram (SP), Welch periodogram (WP), multitaper (MT), Yule-Walker (YW), Burg (BG), and covariance (CV) based ED techniques. The proposed detector showed better performance than the SP, WP, and MT while providing better false alarm performance than the YW, BG, and CV. Data provided here support the effectiveness of the proposed RVNN based ED for CR application

A real valued neural network based autoregressive energy detector for cognitive radio application

A real valued neural network (RVNN) based energy detector (ED) is proposed and analyzed for cognitive radio (CR) application. This was developed using a known two-layered RVNN model to estimate the model coefficients of an autoregressive (AR) system. By using appropriate modules and a well-designed detector, the power spectral density (PSD) of the AR system transfer function was estimated and subsequent receiver operating characteristic (ROC) curves of the detector generated and analyzed. A high detection performance with low false alarm rate was observed for varying signal to noise ratio (SNR), sample number, and model order conditions. The proposed RVNN based ED was then compared to the simple periodogram (SP), Welch periodogram (WP), multitaper (MT), Yule-Walker (YW), Burg (BG), and covariance (CV) based ED techniques. The proposed detector showed better performance than the SP, WP, and MT while providing better false alarm performance than the YW, BG, and CV. Data provided here support the effectiveness of the proposed RVNN based ED for CR application

USER-ACTIVITY DEPENDENT PAGING SCHEME IN A MULTI-CELL CAMPUS WLAN ENVIRONMENT

IEEE 802.11 Wireless Local Area Network (WLAN) is becoming the prevailing technology for the broad band wireless Internet access. However, IEEE 802.11 WLAN has been discovered to be naturally weak in supporting the mobility of mobile host (MH) when there is no traffic to be served for the MHs. Quite a number of commendable works have been done to introduce paging in WLAN and, thereby properly manage scarce network resources such as bandwidth and power. In this work, the authors consider it pertinent to go a step further and design a paging algorithm for campus WLAN, which will take advantage of the unique campus setting and activities. We, therefore, propose a User-Activity Dependent Paging Scheme (UADPS) in a Multi-Cell Campus WLAN Environment; a paging algorithm that considers mobile devices in a multi cell WLAN. This is because we believe that such algorithm will not only be simple to implement, but will make a great positive impact on resource savings for on-campus WLAN users. Results obtained shows that the UADPS utilizes less network resources in searching for an MH when compared to the IEEE 802.11 power save mode algorithm