Advanced metering infrastructure (AMI), as the totality of systems and networks to measure, collect, store, analyze, and use energy usage data, is supposed to be the core component in smart grid. In AMI, there are numerous challenges among which cyber security is a major one that needs to be addressed with priority. The information centric networking (ICN) is a promising architecture for the future Internet that disseminates content based on named data instead of named hosts. The congestion control and self-security can enable more scalable, secure, collaborative, and pervasive networking, these make the ICN a potential network architecture for smart grid. This paper aims to apply the ICN approach on AMI system, which we termed as information centric AMI (ICN-AMI). To the best of our knowledge, this is the first attempt to distribute contents (or requests for contents) based on ICN in AMI system. Moreover, a simulation-based performance evaluation is employed to evaluate the effectiveness of the proposed ICN-AMI approach in traffic control for developing AMI system in smart grid. In addition, we proposed a novel key management scheme (KMS) for a large number of smart meters in this system to ensure confidentiality, integrality, and authentication. To validate the scheme, the security analysis, comparisons are done to demonstrate that the proposed information centric KMS (ICN-KMS) is possible and a promising solution for ICN-AMI system.

Thalassemias are emerging as a global public health concern. Due to remarkable success in the reduction of childhood mortality by controlling infectious diseases in developing countries, thalassemias are likely to be a major public health concern in the coming decades in South Asia. Despite the fact that Bangladesh lies in the world’s thalassemia belt, the information on different aspects (epidemiology, clinical course, mortality, complications and treatment outcomes) of thalassemias is lacking. In this comprehensive review, the aim is to to depict the epidemiological aspects of thalassemias, mutation profile and current treatment and management practices in the country by sharing the experience of dealing with 1178 cases over 2009–2014 time periods in a specialized thalassemia treatment centre. We have also discussed the preventative strategies of thalassemias from the context of Bangladesh which could be effective for other developing countries.

With the proliferation of the Internet's social digital content, sentiment analysis (SA) has gained a wide research interest in natural language processing (NLP). A few significant research has been done in Bangla language domain because of having intricate grammatical structure on text. This paper focuses on SA in the context of Bangla language. Firstly, a specific domain-based categorical weighted lexicon data dictionary (LDD) is developed for analyzing sentiments in Bangla. This LDD is developed by applying the concepts of normalization, tokenization, and stemming to two Bangla datasets available in GitHub repository. Secondly, a novel rule–based algorithm termed as Bangla Text Sentiment Score (BTSC) is developed for detecting sentence polarity. This algorithm considers parts of speech tagger words and special characters to generate a score of a word and thus that of a sentence and a blog. The BTSC algorithm along with the LDD is applied to extract sentiments by generating scores of the two Bangla datasets. Thirdly, two feature matrices are developed by applying term frequency-inverse document frequency (tf-idf) to the two datasets, and by using the corresponding BTSC scores. Next, supervised machine learning classifiers are applied to the feature matrices. Results show that for the case of BiGram feature, support vector machine (SVM) achieves the best classification accuracy of 82.21% indicating the effectiveness of BTSC algorithm in Bangla SA.

This paper represents Quadcopter (QC) as a low-weight and low-cost autonomous flight capable Unmanned Aerial Vehicle (UAV) for delivering parcel ordered by online by using an android device as its core on-board processing unit. This QC by following Google map can locate and navigate destination. This paper demonstrates the QCs capability of delivering parcel ordered by online and coming back to the starting place. The promising result of this method enables future research on using QC for delivering parcel.

In this paper, we present the Intelligent Hybrid MAC (IH-MAC), a novel low power with quality of service guaranteed medium access control protocol for wireless sensor networks (WSNs). The IH-MAC achieves high energy efficiency under wide range of traffic load. It ensures shorter latency to critical and delay-sensitive packets. The IH-MAC protocol achieves high channel utilization during high traffic load without compromising energy efficiency. The IH-MAC does it by using the strength of CSMA and TDMA approach with intelligence. The novel idea behind the IH-MAC is that it uses both the broadcast scheduling and link scheduling. Depending on the network loads, the IH-MAC protocol dynamically switches from broadcast scheduling to link scheduling and vice versa in order to achieve better efficiency. The scheduling is done in the IH-MAC with a novel decentralized approach where the nodes locally use the clock arithmetic to find the time slot, allocated for it. Furthermore, the IH-MAC uses Request-To-Send, Clear-To-send handshakes with methods for adapting the transmit power to the minimum level necessary to reach the intended neighbor. Thus, the IH-MAC reduces energy consumption by suitably varying the transmit power. The IH-MAC also uses the concept of parallel transmission that further reduces delay. The analytical and simulation results corroborate the theoretical idea, and show the efficiency of our proposed protocol.