Maximum convergence algorithm for WiFi based indoor positioning system

WiFi-based indoor positioning is widely exploited thanks to the existing WiFi infrastructure in buildings and built-in sensors in smartphones. The techniques for indoor positioning require the high-density training data to archive high accuracy with high computation complexity. In this paper, the approach for indoor positioning systems which is called the maximum convergence algorithm is proposed to find the accurate location by the strongest receiver signal in the small cluster and K nearest neighbours (KNN) of other clusters. Also, the K-mean clustering is deployed for each access point to reduce the computation complexity of the offline databases. Moreover, the pedestrian dead reckoning (PDR) method and Kalman filter with the information from the received signal strength (RSS) and inertial sensors are applied to the WiFi fingerprinting to increase the efficiency of the mobile object's position. The different experiments are performed to compare the proposed algorithm with the others using KNN and PDR. The recommended framework demonstrates significant proceed based on the results. The average precision of this system can be lower than 1.02 meters when testing in the laboratory environment with an area of 7x7 m using three access points

An automated approach for classifying reverse-engineered and forward-engineered UML class diagrams

UML Class diagrams are commonly used to describe the designs of systems. Such designs can be used to guide the construction of software. In practice, we have identified two main types of using UML: i) FwCD refers to diagrams are hand-made as part of the forward-looking development process; ii) RECD refers to those diagrams that are reverse engineered from the source code; Recently, empirical studies in Software Engineering have started looking at open source projects. This enables the automated extraction and analysis of large sets of project-data. For researching the effects of UML modeling in open source projects, we need a way to automatically determine the way in which UML used in such projects. For this, we propose an automated classifier for deciding whether a diagram is an FwCD or an RECD. We present the construction of such a classifier by means of (supervised) machine learning algorithms. As part of its construction, we analyse which features are useful in classifying FwCD and RECD. By comparing different machine learning algorithms, we find that the Random Forest algorithm is the most suitable algorithm for our purpose. We evaluate the performance of the classifier on a test set of 999 class diagrams obtained from open source projects

Extracting Fetal Electrocardiogram from Being Pregnancy Based on Nonlinear Projection

Fetal heart rate extraction from the abdominal ECG is of great importance due to the information that carries in assessing appropriately the fetus well-being during pregnancy. In this paper, we describe a method to suppress the maternal signal and noise contamination to discover the fetal signal in a single-lead fetal ECG recordings. We use a locally linear phase space projection technique which has been used for noise reduction in deterministically chaotic signals. Henceforth, this method is capable of extracting fetal signal even when noise and fetal component are of comparable amplitude. The result is much better if the noise is much smaller (P wave and T wave can be discovered)

Interactive User-Oriented Views for Better Understanding Software Systems

Abstract Understanding software artefacts is a crucial task for people who want to participate in any software development process. However, because of the large amount of detailed and scattered information in software artefacts, understanding them is usually time-consuming and vulnerable to human errors and subjectivities. A system that aids practitioners to investigate understanding about software artefacts could reduce the vulnerabilities and speed up software development/maintenance process. Our research focuses on building a comprehensive view of software system in order for developers to achieve the two goals: (i) to save the time spending on searching and navigating on source code; and (ii) to gain better understanding about software artefacts regarding to domain-specific tasks. To achieve these goals, we propose an emprical approach in which the visualisation and the generation of high-level design and architectural views from source code and design documentations have been played central roles. The research is on-going and could potentially be extended to di↵erent software artefacts (such as requirements, use-cases, test-cases, revision logs)

Universal Point Estimation, with Applications in Economics, Business and Decision Sciences

Estimation is used widely in numerous disciplines, including Mathematics, Statistics, Economics, Business, and Decision Sciences, among others. Estimation is a process for determining an approximation, which is a value that can be used for a number of purposes, even if input data are sufficient, incomplete, missing or unsecure. In practice, estimation relates to “using the value of a statistic inferred from a sample to estimate the value of a corresponding population parameterâ€. Estimation is usually separated into two categories, namely point estimation and interval estimation. The main purpose of this paper is to present a universal approach to the theory and practice of three methods in statistical inference to obtain point estimates, namely the moment, maximum likelihood, and Bayesian methods. The paper also discusses the advantages and disadvantages of the three universal approaches in practical applications in Economics, Business and Decision Sciences

DESIGN, FABRICATION AND EVALUATION OF LPG-FUEL INJECTION SYSTEM FOR MOTORBIKES

Liquified Petroleum Gas (LPG) fuel is currently an energy source being widely applied in many fields in Vietnam, making a significant contribution to the development of the national economy. This paper presents research results of applying LPG fuel used in motorbikes. The traditional liquid fuel system (gasoline) on a motorbike was replaced by an electronically controlled LPG fuel injection system. LPG fuel is designed to inject into the intake manifold. The injection quantity and injection timing are calculated and controlled by the electronic control unit through the calculation and analysis of the input of key parameters such as intake air pressure and temperature, throttle position, engine speed, and camshaft position. The testing results on real roads in an urban area show that the motorbike operates stably on flat and uphill roads. In addition, the cost of LPG fuel consumption is less than that of the gasoline fuel consumption

Evaluating the layout quality of UML class diagrams using machine learning

UML is the de facto standard notation for graphically representing software. UML diagrams are used in the analysis, construction, and maintenance of software systems. Mostly, UML diagrams capture an abstract view of a (piece of a) software system. A key purpose of UML diagrams is to share knowledge about the system among developers. The quality of the layout of UML diagrams plays a crucial role in their comprehension. In this paper, we present an automated method for evaluating the layout quality of UML class diagrams. We use machine learning based on features extracted from the class diagram images using image processing. Such an automated evaluator has several uses: (1) From an industrial perspective, this tool could be used for automated quality assurance for class diagrams (e.g., as part of a quality monitor integrated into a DevOps toolchain). For example, automated feedback can be generated once a UML diagram is checked in the project repository. (2) In an educational setting, the evaluator can grade the layout aspect of student assignments in courses on software modeling, analysis, and design. (3) In the field of algorithm design for graph layouts, our evaluator can assess the layouts generated by such algorithms. In this way, this evaluator opens up the road for using machine learning to learn good layouting algorithms. Approach.: We use machine learning techniques to build (linear) regression models based on features extracted from the class diagram images using image processing. As ground truth, we use a dataset of 600+ UML Class Diagrams for which experts manually label the quality of the layout. Contributions.: This paper makes the following contributions: (1) We show the feasibility of the automatic evaluation of the layout quality of UML class diagrams. (2) We analyze which features of UML class diagrams are most strongly related to the quality of their layout. (3) We evaluate the performance of our layout evaluator. (4) We offer a dataset of labeled UML class diagrams. In this dataset, we supply for every diagram the following information: (a) a manually established ground truth of the quality of the layout, (b) an automatically established value for the layout-quality of the diagram (produced by our classifier), and (c) the values of key features of the layout of the diagram (obtained by image processing). This dataset can be used for replication of our study and others to build on and improve on this work. Editor\u27s note: Open Science material was validated by the Journal of Systems and Software Open Science Board

Live Poultry Exposures, Hong Kong and Hanoi, 2006

Since 1997, the largest epidemic of highly pathogenic avian influenza (H5N1) ever recorded has caused 172 human and several billion bird deaths. Recently administered questionnaires determined that live poultry exposures have declined by ≈63% in Hong Kong since 2004 and that, in Vietnam, domestic backyard exposures to poultry are likely more important than retail exposures

Influence of foliar application with Moringa oleifera residue fertilizer on growth, and yield quality of leafy vegetables

Biofertilizers produced from organic materials help to promote the growth, and yield quality of crops and is more environmentally friendly than chemical fertilizers. Moringa oleifera is a leafy vegetable whose leaves are also used to make biofertilizers. The use of moringa non-edible parts in biofertilizer preparation remains under-explored. In this study, a procedure to produce moringa foliar biofertilizer (MFB) from non-edible parts was developed. The effect of composting time (3 to 4 months) on the quality of MFB was investigated, and four-month incubation was found suitable for biofertilizers yield with the highest nitrogen content and optimal pH. Furthermore, the influences of MFB doses (20 to 100 mL per Litre) on the growth of lettuce and mustard spinach were studied. The yield of these leafy vegetables was the highest at 100 mL per Litre of MFB spray. Finally, MFB was compared with other commercial foliar sprays, including chitosan fertilizer and seaweed fertilizer. Each foliar treatment was applied every five days until five days before harvest. Plant height, the number of leaves, canopy diameter, leaf area index, actual yield, ascorbic acid content, and Brix were found to be similar in lettuce sprayed with MFB, chitosan, and seaweed fertilizers. In conclusion, the application of MFB promoted the growth and yield of mustard spinach

Effects of palladium on the optical and hydrogen sensing characteristics of Pd-doped ZnO nanoparticles

Abstract The effect of palladium doping of zinc oxide nanoparticles on the photoluminescence (PL) properties and hydrogen sensing characteristics of gas sensors is investigated. The PL intensity shows that the carrier dynamics coincides with the buildup of the Pd-related green emission. The comparison between the deep level emission and the gas sensing response characteristics allows us to suggest that the dissociation of hydrogen takes place at Pd Zn -vacancies ([Pd 2+ (4d 9 )]). The design of this sensor allows for a continuous monitoring in the range of 0-100% LEL H 2 concentration with high sensitivity and selectivity. 126