An Enhanced Pairwise Search Approach for Generating Optimum Number of Test Data and Reduce Execution Time

In recent days testing considers the most important task for building software that is free from error. Since the resources and time is limited to produce software, hence, it is not possible of performing exhaustive tests (i.e. to test all possible combinations of input data.) An alternative to get ride from this type exhaustive numbers and as well to reduce cost, an approach called Pairwise (2 way) test data generation approach will be effective. Most of the software faults in pairwise approach caused by unusual combination of input data.  Hence, the demand for the optimization of number of generated test-cases and reducing the execution time is growing in software industries. This paper proposes an enhancement in pairwise search approach which generates optimum number of input values for testing purposes.  In this approach it searches the most coverable pairs by pairing parameters and adopts one-test-at-a-time strategy for constructing a final test-suite.  Compared to other existing strategies, Our proposed approach is effective in terms of number of generated test cases and of execution time. Keywords:, Software testing, Pairwise testing, Combinatorial interaction testing, Test case generation

Improvement opportunity in Agile Methodology and a survey on the adoption rate of the Improved Methodology

Agile method promotes an iterative process on software development. It is a lightweight process that employs short iterative cycles, actively involve users and developers to establish, prioritize, and verify requirements and rely on a team’s tacit knowledge as opposed to documentation. In this paper we describe the existing agile methodologies and improve its different parameters so that software development industries can adopt it more easily. It describes the improvement of overall understanding of the constituent parts of agile systems development methodologies and some improvement of different parameters. In our proposed method we design a Tool of adoption matrix which will help software development industries for adoption decision solution of the Improved Agile Methodology. We have described the result of different software workshop where the adoption assessment will be used to assess the existing agile system and the improved agile system. The result from this tool will help software industries to apply the improved agile methodologies. Keywords: Agile Methodology, Adoption decision, Adoption assess tool, Improvement of Agile

An OFDMA-based Hybrid MAC Protocol for IEEE 802.11ax

Two types of MAC mechanisms i.e., random access and reservation could be adopted for OFDMA-based wireless LANs. Reservation-based MAC is more appropriate than random access MAC for connection-oriented applications as connectionoriented applications provide strict requirements of traffic demands. On the other hand, random access mechanism is a preferred choice for bursty traffic i.e., data packets which have no fixed pattern and rate. As OFDMA-based wireless networks promise to support heterogeneous applications, researchers assume that applications with and without traffic specifications will coexist. Eventually, OFDMA-based wireless LAN will deploy hybrid MAC mechanisms inheriting traits from random access and reservation. In this article, we design a new MAC protocol which employs one kind of hybrid mechanism that will provide high throughput of data as well as maintains improved fair access policy to the medium among the terminals. The protocol works in two steps, where at step 1 sub-channels are approximately evenly distributed to the terminals and at step 2 terminals within in a subchannel will contend for medium randomly if the total number of terminals of the system is larger than the number of sub-channels. The details of the protocol is illustrated in the paper and we analyze the performance of our OFDMA-based multi-channel hybrid protocol using comprehensive computer simulations. Simulation results validate that our proposed protocol is more robust than the conventional CSMA/CA protocol in terms of throughput, collision reduction and fair access. In addition, the theoretical analysis of the saturation throughput of the protocol is also evaluated using an existing comprehensive model

Design and implementation of intelligent dustbin with garbage gas detection for hygienic environment based on IoT

Rapid population expansion necessitated increased resource use in everyday living. As a result, the pace of trash gen-eration has increased dramatically, affecting the environment's hygiene system and other health concerns. Waste overflows in public spaces, and improved management is necessary. The purpose of this study is to develop a model of an intelligent trashcan for usage in smart cities. Additionally, to identify dangerous gases emitted by dustbins for subsequent management operations, as well as to monitor the amount of trash in the waste bin and warn the municipality through SMS. This system includes two ultrasonic sonar sensors for measuring trash level, a GSM module for sending SMS, three gas sensors for detecting harmful garbage gas, an infrared sensor for counting garbage droplets, and an Arduino Uno for managing all activities. The system notifies you whether the bin is full or empty and can also be controlled by voice command. Additionally, released gas may be monitored to determine the severity of the impairment and to notify the appropriate authorities. Most significantly, it will identify a failed trash drop in the bin and alert the user through alarm for truly considering the reduction of spilled garbage surrounding bins while using the system

A novel hybrid evolutionary mating algorithm for Covid19 confirmed cases prediction based on vaccination

Microorganisms may cause illness when they enter the body, multiply, and spread to other parts. The rapid spread of COVID-19 to neighboring countries is examined in this research. Anticipating a positive COVID-19 occurrence helps in determining risks and creating countermeasures. As a result, developing robust mathematical models with small error margins for predictions is crucial. Based on these findings, a combined method of evaluating confirmed cases of COVID-19 with universal immunization is recommended. First, the best hyperparameter values of the RBF kernel-based LSSVM (least square support vector machine) were determined using the most recent Evolutionary Mating Algorithm (EMA). After that, LSSVM will complete the task of prediction. This hybrid method has been utilized for time series forecasting in Malaysia since the country's immunization program against COVID-19 got underway. We evaluate our results next to those of well-known methodologies in nature-inspired metaheuristics

Internet of Things (IoT) based ECG System for Rural Health Care

Nearly 30% of the people in the rural areas of Bangladesh are below the poverty level. Moreover, due to the unavailability of modernized healthcare-related technology, nursing and diagnosis facilities are limited for rural people. Therefore, rural people are deprived of proper healthcare. In this perspective, modern technology can be facilitated to mitigate their health problems. ECG sensing tools are interfaced with the human chest, and requisite cardiovascular data is collected through an IoT device. These data are stored in the cloud incorporates with the MQTT and HTTP servers. An innovative IoT-based method for ECG monitoring systems on cardiovascular or heart patients has been suggested in this study. The ECG signal parameters P, Q, R, S, T are collected, pre-processed, and predicted to monitor the cardiovascular conditions for further health management. The machine learning algorithm is used to determine the significance of ECG signal parameters and error rate. The logistic regression model fitted the better agreements between the train and test data. The prediction has been performed to determine the variation of PQRST quality and its suitability in the ECG Monitoring System. Considering the values of quality parameters, satisfactory results are obtained. The proposed IoT-based ECG system reduces the health care cost and complexity of cardiovascular diseases in the future

Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)

IoT is the greatest ingenious innovation in the modern era, which can exploit also in mission-critical like the healthcare industry. This paper demonstrates effective monitoring of pregnant women mostly in a rural area of a developing country, with the help of wearable sensing enabled technology, which also notifies the pregnant women and her family about the health conditions. There are many researchers have been researched to reduce the maternal and fetal mortality but the mortality rate is not reducing, where it should be in zero tolerance. This research intended to use machine learning algorithms for discovering the risk level on the basis of risk factors in pregnancy. In this research, an existing dataset (Pima-Indian-diabetes dataset) has been used for the analysis of risk factor and comparison of some machine learning algorithm shows that Logistic Model Tree (LMT) gives the highest accuracy in case of classification and prediction of the risk level. Regardless, few selected pregnant women’s data has been collected (through IoT enabled devices) and the same process also applied for this dataset also by using LMT. Comparison results show that the prediction of risks is the same for the existing and real dataset

Software Quality Assurance Development Using Bayesian Graphical Model and Safe Growth Model

Software quality assurance is a planned and systematic approach to ensure that software processes and products confirms to the established standards, processes, and procedures. The goals of software quality assurance are to improve software quality by appropriately monitoring both software and the development process to ensure full compliance with the established standards and procedures. There are several models for software quality assurance, such as the ISO/IEC 90003, and the capability maturity model integration. As the software in today’s systems grows larger, it has more defects, and these defects adversely affect the safety, security, and reliability of the systems. Software engineering is the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software. Quality is conformance to product requirements and should be free. This research concerns the role of software Quality. Software reliability is an important fact of software quality. It is the probability of failure-free operation of a computer program in a specified environment for a specified time. In software reliability modeling, the parameters of the model are typically estimated from the test data of the corresponding component. This research describes a new approach to the problem of software testing. The approach is based on Bayesian graphical models and presents formal mechanisms for the logical structuring of the software testing problem, the probabilistic and statistical treatment of the uncertainties to be addressed, the test design and analysis process, and the incorporation and implication of test results

Maternal HealthCare Using IoT-Based Integrated Medical Device: Bangladesh Perspective

Purpose: The main purpose of this study is to develop a low-cost integrated medical device. This device will help investigate the risk levels of maternal patients as well will reduce the cost involved in medical diagnosis for poor countries like Bangladesh, where maternal healthcare is a great concern. Methodology: We proposed and developed an integrated medical device that includes all possible sensors to collect raw data from maternal patients. As soon as the data is collected it will be sent to the cloud for processing. In the cloud, there are a set of algorithms (software) for processing raw data received from the device. After processing and analyzing our system will automatically identify the risk levels of those patients. The software is developed in open source code so that in the future it can be updated by researchers. Results: We developed the system and practically collected raw data from patients and uploaded those data to our cloud system. In the cloud, it was processed and the resultant data were presented in the form of graphs. From these graphs, the risk levels were identified. Limitations: The proposed system is developed for maternal patients only. This system needs to be authorized by the health regulatory authority. To make it cost-effective some expensive sensors were not used. Contribution: The main contribution of this study is to minimize the cost involved in maternal healthcare in poor countries like Bangladesh. This, in turn, controls the death of mother and child by improving maternal healthcare facilities