Point Analysis Method Research Articles

Change Point Detection Methods for Locating Activations in Functional Neuronal Images

The most common analysis for fMRI images is activation detection, in which the purpose is to find the locations in the brain that respond to specific functions, such as visual processing or motor functions by providing related stimuli as tasks in the experiment. On the other hand, it is also important to detect the instance the activation is triggered. One of the powerful techniques that can analyze the abnormal behavior of any data is change point (CP) analysis. We suggest that CP detection algorithms also can be used to locate the activations in functional magnetic resonance imaging (fMRI) sequences, as well. Our paper presents a two-fold innovative study in that respect. First, we propose to use CP detection algorithms to locate the activations in fMRI signals as a state-of-art topic. Furthermore, we propose and compare a set of change point analysis methods, a regression-based method (RBM), a statistical method (SM), and a mean difference of double sliding windows method (MDSW)) to locate such points. Second, we apply these methods to the fMRI signals, which are acquired from the real subjects, while they were performing fMRI tasks. Proposed methods were applied to three different fMRI experiments with a motor task, a visual task, and a linguistic task. The analysis shows that the methods find activations in accordance with established methods such as statistical parametric maps (SPM). The acquired up to 94 % results also show that the proposed methods can be used effectively to locate the activation times on fMRI time series.

Influence of Nutrient Supplement in the Single Heavy Metal (Pb2+, Cd2+, Cr3+) Uptake and Mineral Nutrients Absorption by Water Kangkong (Ipomoea aquatica forsk)

The heavy metal contamination in the food crop has posed global concern due to its harmful effects on both humans and animals. Hence, its uptake and bioaccumulation study are in utmost importance. The present study investigated the effects of Cd2+, Pb2+, and Cr3+ stress on mineral contents (K+, Na+, Ca2+, P, Mg2+, Fe2+, Cu2+, Zn2+, and Mn2+) in the different parts of water kangkong (Ipomoea aquatica forsk) by point analysis method. Water kangkong cuttings were grown in tap water supplemented with a very small amount of NPK fertilizer and treated with Pb (NO3)2, Cd (NO3)2∙4H2O, and K2Cr2O7 under two soaking solutions – hydroponics solution and tap water solution. Results revealed that Pb2+, Cd2+, and Cr3+ alter the mineral nutrient absorption of kangkong. Particularly, the approximate concentrations of most mineral ions (K+, Ca+, Fe2+, Zn2+, Cu2+, and Mn2+) in the leaves and stems were reduced by Pb2+, Cd2+, and Cr3+ exposure, thus making kangkong deficient in nutrients when consumed as food. It was also observed that these heavy metals caused a disturbance in K/Ca and K/Na ratios, which could greatly impact water balance. Data also suggest that nutrient optimization may help kangkong to develop tolerance to Cd2+, Pb2+, and Cr3+ and can be a good strategy to alleviate the accumulation of heavy metals by kangkong. The results also indicate that the translocation of ions of Pb, Cd, and Cr from roots to shoots behave differently in the presence of nutrients.

Exploring Links between Online Activism and Real-World Events: A Case Study of the #FeesMustFall

The declaration of free education for the poor and working class by the South African government remains a key result of the two-year #FeesMustFall movement. The campaign was tainted by a few heinous incidents that sought to disrupt its objectives. This study examines the connections between online activism and real-world occurrences by undertaking a longitudinal sentiment analysis of textual conversations on the Twitter platform since no quantitative research has been documented in this regard, particularly on the opinions of social media users and their associated impacts. Between October 15, 2015, and April 10, 2017, 576,583 tweets with the hashtag campaign #FeesMustFall were collected and analyzed using the Valence Aware Dictionary Sentiment Reasoner (VADER). The change point analysis (CPA) method was used to detect various changes in the dataset, and the cumulative sum analysis (CUSUM) method was used to discover changes over time. Results revealed that this online activism sentiment reacted to and reflected real-life events. The sentiment expressed is triangulated with a perceived real-life negative event, which is the burning of the University of Johannesburg (UJ) hall and the library at the University of KwaZulu-Natal (UKZN), thus confirming how Internet activism influenced these real-world events during the #FeesMustFall campaign. The study makes a significant contribution because it is the first longitudinal examination of the #FeesMustFall campaign’s sentiment distribution and variations.

Toward Improving the Efficiency of Software Development Effort Estimation via Clustering Analysis

<i>Introduction</i>: The precise estimation of software effort is a significant difficulty that project managers encounter during software development. Inaccurate forecasting leads to either overestimating or underestimating software effort, which can be detrimental for stakeholders. The International Function Point Users Group&#x2019;s Function Point Analysis (FPA) method is one of the most critical methods for software effort estimation. However, the practice of using the FPA method in the same fashion across all software areas needs to be reexamined. <i>Aim</i>: We propose a model for evaluating the influence of data clustering on software development effort estimation and then finding the best clustering method. We call this model the effort estimation using machine learning applied to the clusters (EEAC) model. <i>Method</i>: We cluster the dataset according to the clustering method and then apply the FPA and EEAC methods to these clusters for effort estimation. The clustering methods we use in this study include five categorical variable criteria (Development Platform, Industrial Sector, Language Type, Organization Type, and Relative Size) and the k-means clustering algorithm. <i>Results</i>: The experimental results show that the estimation accuracy obtaining with clustering consistently outperforms the accuracy without clustering for both the FPA and EEAC methods. Significantly, using the FPA method, the average improvement rate from using clustering as opposed to non-clustered was highest at 58.06%, according to the RMSE. With the EEAC method, this number reached 65.53%. The Industry Sector categorical variable achieves the best accuracy estimation compared to the other clustering criteria and k-means clustering. The improvement in accuracy in terms of the RMSE when applying this criterion is 63.68% for the FPA method and 72.02% for the EEAC method. <i>Conclusion</i>: Better results are obtained through dataset clustering compared to no clustering for both the FPA and EEAC methods. The Industry Sector is the most suitable clustering method among the tested clustering methods.

Complexity of Web-based Application for Research and Community Service in Academic

Research data and community service in academic environment is a very important asset that must be managed properly. They have to be applied synergically in order to obtain as quality standards of higher education. A centralized web-based application designed for research data management and community service have been applied in terms of supporting the managerial of activities. To make the application suitable for users, it is necessary to estimate the size of the software built. This study aimed at measuring the consistency of the apps based on feature point analysis method which is owned by research and community service in Indonesia. Fourteen Modification Complexity Adjustment Factor (MCAF) were used for calculating a program scale with adequate precision. The main cost is determining the quality of application sequentially, which includes measuring the weighted value of feature point components, namely, Crude Function Points (CFPs), calculating the Relative Complexity Adjustment Factor (RCAF), and estimating the Function Point (FP) by using the formula itself. The results depict that the size of application was estimated about 18381 lines using FPA methods and achieved successful estimation with 2.2 percent of deviation.

Analysis of the economic performance of the hotel industry using the break-even method: Case study – Al -Mansour Hotel Company

The break-even point is concerned with studying the relationship between revenues, costs and profits at different levels of production, and it means determining the lowest level of production or level of sales that can be achieved for the company in which revenues are equal to costs as it does not achieve losses or profits, so that the lower the volume of sales at the break-even point, the greater the company's opportunities achieving profits. The study deals with a basic problem embodied in the failure to use the break-even method in the management of hotel companies' activity in the context of the scarcity of scientific studies dealing with this problem in the tourism literature in Iraq. The importance of the study was embodied in the possibility of analyzing the factors affecting the break-even point and the extent of the possibility of applying the break-even method in managing the activity of hotel companies to raise economic efficiency and maximize profits. The study aims to raise the efficiency of the economic performance of hotel activity by maximizing profits and to identify the possibility of practical application of this method in hotel companies. The study relied on the descriptive method and the use of mathematical applications and their mathematical equations on the sample of the study, which was represented in the case study of the Mansour Hotel Company for the years (2018, 2019 and 2020). The study ended with proving the main hypotheses developed, which included the lack of know-how for the management of hotel companies in the use of the break-even point analysis method. The analytical and scientific method for the purpose of maximizing the profits of the company

Study on stage method of reservoir flood season

Due to the influence of the monsoon, river runoff in most of China’s river basins is mainly concentrated in the flood season. The distribution is extremely uneven during the year and between the year. It needs to be fully utilized by the reservoir to bring serious challenges to the daily management. Therefore, analyzing the seasonal variation of storm floods, scientifically and rationally staging the flood season can not only give full play to the comprehensive benefits of the reservoir, but also be an inevitable requirement for coordinating reservoir flood control and power generation. Aiming at the several commonly used methods of flood season staging, the case study is carried out, and the applicable conditions are analyzed. Based on these, three new staging methods are proposed. Among them, the improved change point analysis method adopts the linear and nonlinear joint fitting, which improves the commonly used mean value calculation method. In theory, the non-uniformity and seasonality of the reservoir water are more carefully considered, and the flood season is considered to some extent. The distribution law and continuity of floods along the time course; the projection method has a similar theoretical system with the vector statistical method based on the annual maximum sampling method, both of which are based on the intensity of the points, the difference is the point of the latter is projected on the circumference, the partitioning result is selected by manual experience, and the human influence factor is large. The new method is to project the point on the straight line, and quantitatively gives the partitioning method, and is also applicable to the maximum flow of different sequences. The case of the same time, the dynamic clustering method divides the sample set into several subsets according to the similarity between samples, and has the advantage that the calculation amount is small and the genus of the sample can be changed compared with the system clustering method. The research results can provide reference for the reasonable adjustment of the reservoir flood season.

Determination of Hotel Room Rental Rates during Low Season with the Break-Even Point Analysis Method at Aston Hotels International

This study aims to determine how much room rental rates at Aston Hotel Tanjungpinang during the low season in 2020 using the break-even point analysis method so that the company can increase the room occupancy rate during the low season and not experience business losses, the researcher determines the research subject where the selected resource persons are. have competence and in accordance with data needs, while the sampling technique used is purposive sampling. This research is a qualitative research, the types of data used in this study are secondary data and primary data, while the data collection techniques are obtained through observation, interviews and literature study.Break even point is a condition which indicates that the amount of revenue received by the company (total revenue) is equal to the amount of costs incurred by the company. To achieve a break-even point analysis, the minimum occupancy should reach 81.93% per month, the results calculation of the break-even point analysis or break event point rental rates for room rates with studio type of IDR 403,966, - then for the superior room type of IDR 449,179, -, deluxe room type of IDR 463,694-, the premier deluxe room type is IDR 566,727, - while the junior suite is IDR 566,727, - and the president suite of IDR 750,087, -

Efficiency Analysis of Excavator Nut Inventory Using Economic Order Quantity Method at PT. ABCDE Bekasi-Jawa Barat

Inventory management is one of the keys to the success of the production process in any company, including manufacturing companies. Therefore, determining the optimal amount of inventory is crucial for inventory management. In a production process, sometimes a condition is found where the amount of inventory far exceeds what is needed, so that in the process of implementing the specifications change of an inventory will take quite a long time, this is due to an effort to use up obsolete inventory first, so it is necessary to calculate the optimal value of the company inventory. In this research, using the Economic Order Quantity and Reorder Point analysis method in the POM-QM software, it is expected to determine the optimal value of the purchase amount, Safety Stock, Reorder Point, and the required inventory costs of J950010 nuts. The results showed that although there were differences between the results of the POM-QM calculation and the application in the field, the management of J950010 nut stock is optimal.

Thunor: visualization and analysis of high-throughput dose-response datasets.

High-throughput cell proliferation assays to quantify drug-response are becoming increasingly common and powerful with the emergence of improved automation and multi-time point analysis methods. However, pipelines for analysis of these datasets that provide reproducible, efficient, and interactive visualization and interpretation are sorely lacking. To address this need, we introduce Thunor, an open-source software platform to manage, analyze, and visualize large, dose-dependent cell proliferation datasets. Thunor supports both end-point and time-based proliferation assays as input. It provides a simple, user-friendly interface with interactive plots and publication-quality images of cell proliferation time courses, dose–response curves, and derived dose–response metrics, e.g. IC50, including across datasets or grouped by tags. Tags are categorical labels for cell lines and drugs, used for aggregation, visualization and statistical analysis, e.g. cell line mutation or drug class/target pathway. A graphical plate map tool is included to facilitate plate annotation with cell lines, drugs and concentrations upon data upload. Datasets can be shared with other users via point-and-click access control. We demonstrate the utility of Thunor to examine and gain insight from two large drug response datasets: a large, publicly available cell viability database and an in-house, high-throughput proliferation rate dataset. Thunor is available from www.thunor.net.

Delineating the Urban Areas of a Cross-Boundary City with Open-Access Data: Guangzhou–Foshan, South China

Cities defined mainly from the administrative aspect can create impact and problems especially in the case of China. However, only a few researchers from China have attempted to identify urban areas from the morphology dimension. In addition, previous studies have been mostly based on the national and regional scales or a single prefecture city and have completely ignored cross-boundary cities. Defining urban areas on the basis of a single data type also has limitations. To address these problems, this study integrates point of interest and nighttime light data, applies the breaking point analysis method to determine the physical geographic scope of the Guangzhou–Foshan cross-border city, and then compares this city with Beijing and Shanghai. Results show that Guangzhou–Foshan comprises one core urban area and six suburban counties, among which the core urban area extends across the administrative boundaries of Guangzhou and Foshan. The urban area and average urban radius of Guangzhou–Foshan are larger than those of Beijing and Shanghai, and this finding contradicts the city size measurements based on the administrative division system of China and those published on traditional official statistical yearbooks. In terms of urban density value, Shanghai has the steepest profile followed by Guangzhou–Foshan and Beijing, and the profile line of Guangzhou–Foshan has a bimodal shape.

Early and quick function points analysis: Evaluations and proposals

Measuring Function Points following the standard process is sometimes long and expensive. To solve this problem, several early estimation methods have been proposed. Among these, the “NESMA Estimated” method is one of the most widely used; it has also been selected by the International Function Point User Group as the official early function point analysis method, under the name of ‘High-level FPA’ method. A large-scale empirical study has shown that the High-level FPA method – although sufficiently accurate – tends to underestimate the size of software. Underestimating the size of the software to be developed can easily lead to wrong decisions, which can even result in project failure. In this paper we investigate the reasons why the High-level FPA method tends to underestimate. We also explore how to improve the method to make it more accurate. Finally, we propose size estimation models built using different criteria and we evaluate the estimation accuracy of these new models. Our results show that it is possible to derive size estimation models from historical data using simple regression techniques: these models are slightly less accurate than those delivered by the High-level FPA method in terms of absolute estimation errors, but can be used earlier than the High-level FPA method, are cheaper, and do not underestimate software size.

A threshold LC–MS/MS method for 92 analytes in oral fluid collected with the Quantisal® device

A study of impaired driving rates in the province of Québec is currently planned following the legalization of recreational cannabis in Canada. Oral fluid (OF) samples are to be collected with a Quantisal® device and sent to the laboratory for analysis. In order to prepare for this project, a qualitative decision point analysis method monitoring for the presence of 97 drugs and metabolites in OF was developed and validated.This high throughput method uses incubation with a precipitation solvent (acetone:acetonitrile 30:70 v:v) to boost drug recovery from the collecting device and improve stability of benzodiazepines (e.g., α-hydroxyalprazolam, clonazepam, 7-aminoclonazepam, flunitrazepam, 7-aminoflunitrazepam, N-desmethylflunitrazepam, nitrazepam). The Quantisal® device has polyglycol in its stabilizing buffer, but timed use of the mass spectrometer waste valve proved sufficient to avoid the glycol interferences for nearly all analytes. Interferences from OF matrices and 140 potentially interfering compounds, carryover, ion ratios, stability, recovery, reproducibility, robustness, false positive rate, false negative rate, selectivity, sensitivity and reliability rates were tested in the validation process. Five of the targeted analytes (olanzapine, oxazepam, 7-aminoclonazepam, flunitrazepam and nitrazepam) did not meet the set validation criteria but will be monitored for identification purposes (no comparison to a cut-off level).Blind internal proficiency testing was performed, where six OF samples were tested and analytes were classified as “negative”, “likely positive” or “positive” with success. The final validated OF qualitative decision point method covers 92 analytes, and the presence of 5 additional analytes is screened in this high throughput analysis.

Synthesis, characterization, acetylcholinesterase inhibition, and molecular docking studies of new piperazine substituted dihydrofuran compounds

Novel unsaturated piperazine and homopiperazine derivatives (3a–h) were synthesized in medium to good yields by acylation reactions of piperazine and homopiperazine with methacrylic anhydride (2a) and benzoyl chloride (2b). Piperazine containing dihydrofuran compounds (5a–l) were obtained from radical addition and cyclizations of 3a–h with 1,3-dicarbonyl compounds such as dimedone (4a), ethyl acetoacetate (4b) and acetylacetone (4c) mediated by Mn(OAc)3 for the first time. While the reaction of 3b (1-methacryloylpiperazine) with 4a and 4b gave bis-dihydrofurans (5b and 5d) beside mono-dihydrofurans (5a and 5c), the reaction of 3b–e, 3g, 3h, and 3e with 1,3-dicarbonyl compounds gave mono dihydrofuran compounds (5f–l) in medium to high yields. Structures of all novel compounds were determined by melting point analysis, 1H NMR, 13C NMR, HRMS, and FTIR methods. All piperazine containing dihydrofuran compounds were evaluated for their inhibitory activities toward acetylcholinesterase (AChE) by Ellman method and IC50 values were presented. Compounds 5c, 5d, 5e, 5i, and 5l show highest inhibitory activities with IC50 values of 5.79, 3.89, 5.07, 4.30, and 2.24 µM, respectively. In addition, molecular docking studies were performed on selected structures 5d, 5i, and 5l to investigate ligand–protein interactions. Binding energies were calculated and compared with standart drug donepezil.

Determination of value price or computer application using function point analysis method

Some developer very capable of developing good quality working applications, but they don’t have the right value and price for their products, and it is because they did not use the right method to calculate the size of the product and valuate them correctly, most of them use analogy and expert judgment to perform their product sizing and valuation. This situation will create inconsistency in doing the pricing and it will create disadvantages for both developers and users. Function point analysis provides a methodology to perform software size calculation using algorithmic approaches that gives comprehensive and consistent results. In this document, I will explain step by step the processes of calculating the Function point using FPA procedures by implementing calculation formula of EI, EO, EQ, ILF, EIF, and VAP. I also will implement them to calculate the size of the “XIbar” application system, especially module customer care and customer info. By doing all these activities I hope will provide simple templates and procedures for calculating the size of application software that can be used easily by developers, students, and others who need it.

Spectral Characteristic Analysis and Remote Sensing Classification of Coastal Aquaculture Areas Based on GF-1 Data

Zhu, H.; Li, K.; Wang, L.; Chu, J.; Gao, N., and Chen, Y., 2019. Spectral characteristic analysis and remote sensing classification of coastal aquaculture areas based on GF-1 data. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 49-57. Coconut Creek (Florida), ISSN 0749-0208.In this research, the offshore area of Bohai Sea, which is located at Yantai City in Shandong Province, was selected as the experimental region and the GF-1 data was used as experimental data. First, the spectral characteristics of different target objects in the study area were investigated using the sample point analysis method. The corresponding spectral discriminant function was also constructed. Second, the object-oriented multi-scale segmentation method was employed to perform the object segmentation of GF-1 image. Finally, the image segmentation results were classified through the constructed discriminant function of the spectral characteristics of target objects. The remote sensing classification results of coastal aquaculture areas were also obtained. The overall accuracy of such classification results was 91.6 %. Compared with traditional classification methods, classification accuracy improved greatly and the classified aquaculture types increased.

Analisis Strategi E-Marketing Dalam Upaya Peningkatan Penjualan Travel Agent Online mybaliwisata.com

Every year the graph of foreign and domestic tourist arrivals to Bali continues to increase. This is a great opportunity to increase tourist destination visits to Bali. The role of technology will answer the problems that exist in this era of globalization by using computerized systems, so that the use of information technology helps effectiveness and efficiency in working on information system processes. After analyzing the Business Model Canvas (BMC) and E-marketing Business data using social media, the results obtained were an increase in sales of mybaliwisata.com online travel agents in increasing sales turnover. This study uses the Break Event Point (BEP) analysis method to calculate the valuation of mybaliwisata.com online travel agent company, so that optimization of the increase in mybaliwisata.com Travel Agent Online sales can be done well.

Analysis of Black Spot of Traffic Accident in Wuhan Port

The proposal to build the “Yangtze River Golden Waterway” strategy has enabled the shipbuilding volume of the Yangtze River trunk to grow rapidly. With the increase of ship traffic flow, the Yangtze River water traffic safety is facing severe challenges. This paper draws on the road traffic black spots and existing research methods of water traffic accidents and the definition of water traffic black spots. The DBSCAN algorithm and the accident-level weighted average method are used to establish the blackpoint identification model for waterborne traffic. The model is applied to the Yangtze River mid-stream Wuhan Port 2013-2017 water traffic safety accident as an example. Ten black spots and corresponding boundaries are identified. The black point analysis method used in this paper can effectively quantitatively analyze the spatial distribution and characteristics of water traffic black spots, which can provide a new theoretical basis for ensuring the safety of water traffic.

Novel phase diagrams of aqueous two-phase systems based on 1,4-bis-(2-hydroxypropyl)-piperazine + Na2CO3 + H2O: Equilibrium data and correlation

Aqueous two-phase system (ATPS) has been regarded as a potential method for removing heat-stable salts (HSS) in 1, 4-bis-(2-hydroxypropyl)-piperazine (HPP). In this work, the binodal and liquid-liquid equilibrium data of the HPP + Na2CO3 + H2O system have been determined by cloud point and phase component analysis methods at a series of temperatures. It is well revealed that the effect of temperature on the system presents minor variations in the biphasic region. The binodal data are fitted by polynomial and empirical equations, and NRTL model is employed for fitting the liquid-liquid equilibrium data. The results reveal that the binodal data is adequately correlated with the empirical equation, with a correlation coefficient R2 greater than 0.99 and standard deviations (SD) less than 0.02%. The NRTL model is in good accordance with the liquid-liquid equilibria data, with a relative root mean square deviations (RMSD) between the calculated and the experimental values are lower than 1.70%, and the average absolute deviations (AAD) are lower than 1.30%. Thereby, the parameters of equations and NRTL model are consistent with the actual calculation and engineering application requirements. The ATPS method for removing HSS is expected to be applied for other CO2 capture process using alcohol amines as absorbents.

Detecting Multiple Change Points Using Adaptive Regression Splines With Application to Neural Recordings.

Time series, as frequently the case in neuroscience, are rarely stationary, but often exhibit abrupt changes due to attractor transitions or bifurcations in the dynamical systems producing them. A plethora of methods for detecting such change points in time series statistics have been developed over the years, in addition to test criteria to evaluate their significance. Issues to consider when developing change point analysis methods include computational demands, difficulties arising from either limited amount of data or a large number of covariates, and arriving at statistical tests with sufficient power to detect as many changes as contained in potentially high-dimensional time series. Here, a general method called Paired Adaptive Regressors for Cumulative Sum is developed for detecting multiple change points in the mean of multivariate time series. The method's advantages over alternative approaches are demonstrated through a series of simulation experiments. This is followed by a real data application to neural recordings from rat medial prefrontal cortex during learning. Finally, the method's flexibility to incorporate useful features from state-of-the-art change point detection techniques is discussed, along with potential drawbacks and suggestions to remedy them.