THE EFFECTS OF AUTHENTIC PEDAGOGICAL PRACTICES ON STUDENTS’ EDUCATIONAL PERFORMANCES AND RETENTION POWER

In-practice traditional lecture, discussion and assignments based pedagogical practices play its role in students’ learning and retention power. The current study intends to investigate whether authentic pedagogical practices are more effective in terms of enhancing students’ educational performances and retention power or the traditional pedagogical practices. Therefore, this study focused on investigating the effects of authentic and traditional pedagogical practices on students’ educational performances and retention power at secondary level. The objective was to measure the effects of authentic and traditional pedagogical practices on students’ educational performances and retention power. A pre-test post-test comparative group design was adopted to conduct the study. The students of experimental group were exposed to authentic pedagogical practices while the control group was treated on traditional routine pedagogical practices. Data from the experimental and control group were collected through a self-developed test. Thrice was the test administered to both groups, the collected data were analyzed through Mean, Standard Deviation and independent sample t-test. Results of the study concludes that students of experimental group performed higher on the post-test than the students of control group, the performance of experimental group was also better as compared to the control group on the test of retention power. Keeping in view the results that data yielded, it was recommended that teachers at secondary level may follow authentic pedagogical practices as compared to other traditional ones. Based on the findings of the study relevant and applicable recommendations were made

A Correlational Study on Teacher Educators’ Assessment Literacy and Their Students’ Academic Achievement

The knowledge and skills of classroom assessment is one of the requirements which have been declared in National Professional Standards for Teachers in Pakistan. Without the knowledge and skills of assessment teachers cannot effectively implement their instructional plan. This study investigated teacher educators’ assessment literacy and its relationship with the academic achievement of prospective teachers. The study was quantitative correlational and survey method was adopted for data collection. Teacher educators and prospective teachers of Government Colleges of Elementary Teachers and Regional Institute for Teacher Educators were included in the population. Data were collected through an assessment literacy test from the sample groups of the study which was analyzed through mean scores, Pearson correlation and linear regression. The results illustrated that the assessment literacy of teacher educators was of average level which was significantly co-related to the academic achievement of prospective teachers. To further enhance the assessment literacy in-service trainings/workshops were recommended. Further, an Assessment Wing at federal level for the development of assessment standards at different level was also recommended

Cluster-based cooperative subcarrier sensing using antenna diversity-based weighted data fusion

Cooperative spectrum sensing (CSS) is used in cognitive radio (CR) networks to improve the spectrum sensing performance in shadow fading environments. Moreover, clustering in CR networks is used to reduce reporting time and bandwidth overhead during CSS. Thus, cluster-based cooperative spectrum sensing (CBCSS) has manifested satisfactory spectrum sensing results in harsh environments under processing constraints. On the other hand, the antenna diversity of multiple input multiple output CR systems can be exploited to further improve the spectrum sensing performance. This paper presents the CBCSS performance in a CR network which is comprised of single- as well as multiple-antenna CR systems. We give theoretical analysis of CBCSS for orthogonal frequency division multiplexing signal sensing and propose a novel fusion scheme at the fusion center which takes into account the receiver antenna diversity of the CRs present in the network. We introduce the concept of weighted data fusion in which the sensing results of different CRs are weighted proportional to the number of receiving antennas they are equipped with. Thus, the receiver diversity is used to the advantage of improving spectrum sensing performance in a CR cluster. Simulation results show that the proposed scheme outperforms the conventional CBCSS scheme

Peak to average power ratio reduction in NC–OFDM systems

Non contiguous orthogonal frequency division multiplexing (NC-OFDM) is an efficient and adaptable multicarrier modulation scheme to be used in cognitive radio communications. However like OFDM, NC-OFDM also suffers from the main drawback of high peak to average power ratio (PAPR). In this paper PAPR has been reduced by employing three different trigonometric transforms. Discrete cosine transform (DCT), discrete sine transform (DST) and fractional fourier transform (FRFT) has been combined with conventional selected level mapping (SLM) technique to reduce the PAPR of both OFDM and NC-OFDM based systems. The method combines all the transforms with SLM in different ways. Transforms DCT, DST and FRFT have been applied before the SLM block or inside the SLM block before IFFT. Simulation results show the comparative analysis of all the transforms using SLM in case of both OFDM and NC-OFDM based systems

Cooperative subcarrier sensing using antenna diversity based weighted virtual sub clustering

The idea of cooperation and the clustering amongst cognitive radios (CRs) has recently been focus of attention of research community, owing to its potential to improve performance of spectrum sensing (SS) schemes. This focus has led to the paradigm of cluster based cooperative spectrum sensing (CBCSS). In perspective of high date rate 4th generation wireless systems, which are characterized by orthogonal frequency division multiplexing (OFDM) and spatial diversity, there is a need to devise effective SS strategies. A novel CBCSS scheme is proposed for OFDM subcarrier detection in order to enable the non-contiguous OFDM (NC-OFDM) at the physical layer of CRs for efficient utilization of spectrum holes. Proposed scheme is based on the energy detection in MIMO CR network, using equal gain combiner as diversity combining technique, hard combining (AND, OR and Majority) rule as data fusion technique and antenna diversity based weighted clustering as virtual sub clustering algorithm. Results of proposed CBCSS are compared with conventional CBCSS scheme for AND, OR and Majority data fusion rules. Moreover the effects of antenna diversity, cooperation and cooperating clusters are also discussed

Peak to average power ratio based spatial spectrum sensing for cognitive radio systems

The recent convergence of wireless standards for incorporation of spatial dimension in wireless systems has made spatial spectrum sensing based on Peak to Average Power Ratio (PAPR) of the received signal, a promising approach. This added dimension is principally exploited for stream multiplexing, user multiplexing and spatial diversity. Considering such a wireless environment for primary users, we propose an algorithm for spectrum sensing by secondary users which are also equipped with multiple antennas. The proposed spatial spectrum sensing algorithm is based on the PAPR of the spatially received signals. Simulation results show the improved performance once the information regarding spatial diversity of the primary users is incorporated in the proposed algorithm. Moreover, through simulations a better performance is achieved by using different diversity schemes and different parameters like sensing time and scanning interval

Time-constrained nature-inspired optimization algorithms for an efficient energy management system in smart homes and buildings

This paper proposes two bio-inspired heuristic algorithms, the Moth-Flame Optimization (MFO) algorithm and Genetic Algorithm (GA), for an Energy Management System (EMS) in smart homes and buildings. Their performance in terms of energy cost reduction, minimization of the Peak to Average power Ratio (PAR) and end-user discomfort minimization are analysed and discussed. Then, a hybrid version of GA and MFO, named TG-MFO (Time-constrained Genetic-Moth Flame Optimization), is proposed for achieving the aforementioned objectives. TG-MFO not only hybridizes GA and MFO, but also incorporates time constraints for each appliance to achieve maximum end-user comfort. Different algorithms have been proposed in the literature for energy optimization. However, they have increased end-user frustration in terms of increased waiting time for home appliances to be switched ON. The proposed TG-MFO algorithm is specially designed for nearly-zero end-user discomfort due to scheduling of appliances, keeping in view the timespan of individual appliances. Renewable energy sources and battery storage units are also integrated for achieving maximum end-user benefits. For comparison, five bio-inspired heuristic algorithms, i.e., Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search Algorithm (CSA), Firefly Algorithm (FA) and Moth-Flame Optimization (MFO), are used to achieve the aforementioned objectives in the residential sector in comparison with TG-MFO. The simulations through MATLAB show that our proposed algorithm has reduced the energy cost up to 32.25% for a single user and 49.96% for thirty users in a residential sector compared to unscheduled load

Internet Protocol/MultiProtocol Label Switching (IP/MPLS) Networks

This paper discusses different aspects of Multi-Protocol Label Switching (MPLS) networks. In this paper, we first discussed MPLS in detail, the technology was developed to advance the IP network

Examination of Temperature Variability over Lahore (Pakistan) and Dhaka (Bangladesh): A Comparative Study

Lahore and Dhaka are rapid expanding and over populated cities of South Asia located in Pakistan andBangladesh respectively. The present study focuses on the evaluation of temperature variability in comparison of bothcities. This study primarily aims at the assessment and examination of temperature variations in both mega cities ofSouth Asia which are seasonal as well as the annual. The time series data were analysed by using statistical techniquesAutoregressive Moving Average Model (ARMA) and Autoregressive Integrated Average Model (ARIMA). The resultsreveal that the minimum temperature is increasing much faster than that of the maximum temperature of both cities.However, the temperature rise(in maximum and minimum) has been observed highest during the spring seasons in bothcities