An Interplay of Oral and Written Communication and Performance of Undergraduates

Students' proper use of oral and written communication plays a vital role in elevating their performance at the higher education level. Therefore, this study was conducted to explore the interplay of these communication types with the performance of undergraduates. A five point Likert-type scale was administered on a sample of 540 Bahauddin Zakariya University, Multan enrolled in the BS program of three faculties (Social Sciences, Sciences, and Languages). Students' performance was assessed by their CGPA (Cumulative Grade Point Average) in previous semesters, further correlated with their communication skills. All respondents were selected from three semesters of the BS program from twelve departments whose total population was two thousand two hundred and twenty-nine. For the analysis of data, mean and standard deviation were used as descriptive statistics, while Pearson's Product Moment and one-way ANOVA were used as inferential statistics. After analysis, a statistically significant positive correlation between CGPA and written communication was revealed However, no statistically significant interplay was found between CGPA and oral communication. It was found that there is no statistically significant difference in mean scores of students of different faculties on oral and written communication. Keywords: Interplay, Oral, Written Communication, Performance, Undergraduates

Radial Basis Kernel Regressive Feature Extraction and Robert Ensembled Brown Boost Classifier for Attack Detection in Cloud Environment

Cloud computing shares the resource in information technology field. The existing technique is failed to provide better results for identifying unknown attacks with higher accuracy and lesser time consumption. In order to address these problems, Radial Basis Kernel Regressive Feature Extracted Brown Boost Classification (RBKRFEBBC) method is introduced for performing the attack detection in cloud computing. The main objective of RBKRFEBBC method is to improve the attack detection performance with higher accuracy and minimal time consumption. Dichotomous radial basis kernelized regressive function is used in RBKRFEBBC method to extract the relevant features through determining the correlation between the output and one or more input variables (i.e., features of patient transaction data). After extracting relevant features, GRNBBC algorithm is used in RBKRFEBBC method to improve the secured data communication performance through classifying the patient data transaction as attack presence or attack absence. By this way, attack detection is carried out in accurate manner. Experimental evaluation is carried out by NSL-KDD dataset using different metrics like attack detection accuracy, attack detection time and error rate. The evaluation result shows RBKRFEBBC method improves the accuracy and minimizes the time consumption as well as error rate than existing works.

Communication Performance vs. Implementation Trade-offs of Interpolation Techniques for FFT-Based Carrier Synchronization exemplified on DVB-RCS2

Carrier synchronization is a crucial part of any wireless receiver, which is required due to frequency and phase offset. In case of transmission in a Time Division Multiple Access system the carrier synchronization has to be carried out for every burst separately. The DVB-RCS2 standard specifies a large variety of reference burst types with very limited known symbols. For each of these types a thorough exploration of different synchronization algorithms is required to find a trade-off between a good communication performance at very low Signal to Noise Ratio (SNR) and an efficient hardware implementation. A state-of-the-art algorithm for carrier synchronization is based on the so called Fast Fourier Transformation (FFT). An inherit limitation for the precision of frequency estimation is given by the FFT point size. To counteract this limitation, the FFT point size must be increased. In this paper we extensively compare two possible interpolation techniques for FFT results in three FFT-based carrier synchronization methods. These are applied to various reference burst types specified in the DVB-RCS2 standard. The trade-offs of these combinations are identified with a special focus on hardware implementation efficiency. Furthermore, we present a flexible IP core which can process the three synchronization methods in an efficient way and analyze its implementation complexity and throughput on a Xilinx Kintex FPGA.

An improved Whale Optimization Approach for Effective Data Transmission for IoT Communication

Internet of Things (IoT) offers interconnection among several wireless communication devices for the provision of device accessibility and in-built capacity. IoT provides device interaction and provision of advantages capability for networking and socialization with consideration of intermediate devices. Through innovation in technology IoT devices convert cyber environments with hyper-connectivity. IoT communication contains several smart devices such as body sensors, smartphones, tags, electronic gadgets, and so on. IoT communication is involved in the provision of heterogeneous connectivity among devices for the provision of interface and connectivity for enhancing service quality. The data sending among IoT devices is affected by several threats that have an impact on the network’s performance. To overcome the limitation related to IoT communication, it is necessary to develop an appropriate technique for enhancing IoT network communication performance. In this research developed a multi-channel routing approach is adopted in IoT communication. The developed approach utilizes a meta-heuristics approach with probability-based characteristics. For the meta-heuristics approach this research utilizes whale optimization technique combined with probability characteristics for improving the IoT communication performance of the network. The proposed approach utilizes initially constructs the IoT communication path for information sharing and gathering. This path information is identified through the objective function of a meta-heuristic approach. Based on the objective function hoping between the devices is minimized through which data are transmitted in the network. Simulation is performed as a unique proposed approach with a coverage area of 100 meters. For identification of the optimal path in the network, WOA identifies the path of communication through probability function. Comparative analysis of research exhibited that WOA provides significant performance with the identification of optimal value at the range of 1.0746e-78. Further, the proposed probability-based WOA approach significantly improves the performance of the IoT network.

Light-Based IoT: Developing a Full-Duplex Energy Autonomous IoT Node Using Printed Electronics Technology

The light-based Internet of things (LIoT) concept defines nodes that exploit light to (a) power up their operation by harvesting light energy and (b) provide full-duplex wireless connectivity. In this paper, we explore the LIoT concept by designing, implementing, and evaluating the communication and energy harvesting performance of a LIoT node. The use of components based on printed electronics (PE) technology is adopted in the implementation, supporting the vision of future fully printed LIoT nodes. In fact, we envision that as PE technology develops, energy-autonomous LIoT nodes will be entirely printed, resulting in cost-efficient, flexible and highly sustainable connectivity solutions that can be attached to the surface of virtually any object. However, the use of PE technology poses additional challenges to the task, as the performance of these components is typically considerably poorer than that of conventional components. In the study, printed photovoltaic cells, printed OLEDs (organic light-emitting diodes) as well as printed displays are used in the node implementation. The dual-mode operation of the proposed LIoT node is demonstrated, and its communication performance in downlink and uplink directions is evaluated. In addition, the energy harvesting system’s behaviour is studied and evaluated under different illumination scenarios and based on the results, a novel self-operating limitation aware algorithm for LIoT nodes is proposed.

The Accuracy of Business English Curriculum to Students’ Communication Performance: The EFL Students’ Perception

Measuring the accuracy of a private university in Batam Business English course curriculum to the present needs of workplaces in Batam from students’ perception is essential. Because 85% of the university students are working, it is compulsory to maintain the gap low between what students learned in class and what is implemented in the working field. A questionnaire consists of three dimensions (curriculum, communication performance, and motivation) distributed randomly to 60 students from a population (N=328) of the third-semester students programmed Business English course at a private university in Batam. The result suggested that the curriculum needs to add more practices, peer work, and case studies to improve students’ communication performance. Students’ perspectives in the Business English course reflected a new technical vocabulary that needed to practice in a correlated context. The curriculum content’s relevance to the workplace’s contextual needs is moderately related because not all working students used the English language in their workplace. Additional focus on internal and external motivation through group work and peer work is needed to improve students’ communication performance and confidence. Finally, the existing Business English curriculum is reasonably accurate, supporting students’ communication performance, both written and oral, at their workplace.

Pelayanan Komunikasi Pemerintahan Dalam Pemberitaan Kebijakan Pemerintah Daerah Kepada Stakeholder di Kalimantan Selatan

This study was conducted in the midst of the lack of studies on local government communication in developing countries. Existing studies tend to attribute performance in this area to central government. The contribution of this study is related to exploring the practice of government communication in the context of local government in countries towards democracy. The author uses the communication of the local government of South Kalimantan Province in its services to stakeholders as a case study. The results of the analysis of various documents, observations and in-depth interviews related to the communication performance of local government in South Kalimantan from January to October 2020 were compiled and analyzed using Miles and Huberman data analysis techniques. In conclusion, the results of the study show that the quality of local government communication is influenced by various factors, both structural and management. Although management factors remain important, in the case of South Kalimantan, structural factors have more influence on local government communications. While the communication performance of local government has not involved active participation from the bottom, it is more elite-oriented than public-oriented. Local government officials are less responsive and still communicate downward, so that the ideas of professionalizing local government communication are still limited to expectations rather than reality. This study recommends that local government communication can be effective if it is participatory, ie has a vision and mission of community empowerment and citizen involvement in participation for local government policy planning and implementation.

An Intelligent Multimode Clustering Mechanism Using Driving Pattern Recognition in Cognitive Internet of Vehicles

Connected autonomous vehicles can leverage communication and artificial intelligence technologies to effectively overcome the perceived limitations of individuals and enhance driving safety and stability. However, due to the high dynamics of the vehicular network and frequent interruptions and handovers, it is still challenging to provide stable communication connections between vehicles, which is likely to cause disasters. To address this issue, in this paper, we propose an intelligent clustering mechanism based on driving patterns in heterogeneous Cognitive Internet of Vehicles (CIoVs). In the proposed approach, we analyze the driving mode containing multiple feature parameters to accurately capture the driving characteristics. To ensure the accuracy of pattern recognition, a genetic algorithm-based neural network pattern recognition algorithm is proposed to support the reliable clustering of connected autonomous vehicles. The cognitive engines recognize the driving modes to group vehicles with a similar driving mode into a relatively stable cluster. In addition, we formulate the stability and survival time of clusters and analyze the communication performance of the clustering mechanism. Simulation results show that the proposed mechanism improves the reliable communication throughput and average cluster lifetime by approximately 14.4% and 11.5% respectively compared to the state-of-the-art approaches.

Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings

Symmetry-based channel digital twin is a great technology which can reproduce the communication channel of real scenes for performance evaluation of the wireless sensor network (WSN) inside tower buildings, based on the ray tracing (RT) method and machine learning (ML) theories, a cluster-based channel model is proposed in this paper. Meanwhile, an improved k-means method, which considers the weight of different dimensions in the multipath component distance (MCD) is presented for clustering, which has better clustering performance over the sparsity-based algorithm and traditional k-means algorithm. Moreover, the channel parameters such as cluster delay and cluster power are also investigated. On this basis, the communication performance of WSN, i.e., bit error rate (BER) and channel capacity are derived and analyzed. The simulation and analysis results show that the cluster model based on the RT method can get approximately equivalent channel impulse response (CIR), and the BER of proposed model is consistent with the simulated one. These results can provide reference for the node layout and optimization of WSN inside tower buildings.