Trend Analysis Tool Research Articles

Analysis of Trends in Children"s Language-related Research Using Research Trend Analysis Tools

Analysis of Trends in Children"s Language-related Research Using Research Trend Analysis Tools

Evolution characteristics and performance evaluation of extended end-plate joints with single and double side connections under cyclic loading

Experimental studies were conducted on four extended end-plate joints subjected to cyclic loading at the column top, investigating the evolving patterns of the joints' mechanical performance. The paper provides a detailed analysis and discussion of the test joints' failure modes, ductility, stiffness degradation, and energy dissipation capacity. The Mann-Kendall (M − K) trend analysis tool was applied to the mechanical response curves, identifying key performance evolution points (evolution initiation point P and overall yield point Q). The trends in bolt forces, deformations, and strains at critical joints were effectively validated, revealing the transition of the energy system from quantitative to qualitative changes and the component's failure process from stability to instability. Additionally, based on the experimental joints' hysteresis curves and energy dissipation capacity, a theoretical hysteresis model was established to predict the joint's hysteresis curve and cumulative dissipated energy accurately. According to EC3 requirements, joints were classified as partially rigid connections. The experimental results of the initial rotational stiffness and plastic moment were further used to evaluate the calculated values in existing standards EN 1993-1-8, ANSI/AISC 358-16, and GB 51017-2017. The results indicate that extended end-plate connections possess sufficient strength, joint rotational stiffness, ductility, and energy dissipation capacity, making them suitable for seismic moment frames.

Trend Study of GP – Google Pay

In this modern world, everyone is updated with new technologies which make people’s work easier. Nowadays, we can find almost everything on the internet – from food to clothes and many more. But, for that, we have to pay money. How do we do that safely and securely? One of the ways to pay is through digital payments. Many companies which are pioneers in the digital industry offer such ways for people which is very useful. Such solutions minimize some risks and provide benefits to the users. This research is carried out on Google Pay- one of the pioneers in providing such solutions. Many companies are providing such solutions. But how Google Pay stands alone and gets benefits is analyzed by the researcher. The financial statement of the company will provide us with the necessary details to carry out this analysis. People prefer user-friendly payment solutions and this increases demand for such platforms. This research helps the company to know its trend based on its previous performance and can predict the future trend. The trend analysis tool is used to analyze the company’s operations and performance. Key Word: Digital payments, Financial Statements, Trend Analysis, user-friendly, demand, Platforms

Continuous Glucose Monitoring Sensor Glucose Data Analysis of Time in Range, Time Above Range, Time Below Range and Waveform Comparison Study of Time in Range Curve Against both Average Daily Glucose Curve and Glucose Fluctuation Curve for a 3.3 Year Period based on GH-Method: Math-Physical Medicine (No. 500)

The author applies quantitative pattern and trend analysis tools using his collected continuous glucose monitoring (CGM) sensor data during a 3.3 year period from 5/8/2018 to 8/25/2021. Special attention has been placed on applying the American Diabetes Association (ADA) 2020 Guidelines for Time In Range (TIR) % with TIR average glucose values, Time Above Range (TAR) % with TAR average glucose value, and Time Below Range (TBR) % with TBR average glucose value. The purpose of this article is to study the correlations between the TIR curve and both average daily glucose curve (eAG) and glucose fluctuation curve (GF). GF is defined as the difference between the maximum glucose and the minimum glucose within one day or 24 hours duration. This GF term expresses the same meaning as the glycemic variability (GV) used by some diabetes research scientists. However, the author prefers GF over GV since GF describes the amplitude of glucose excursion in an exact and most direct way. Depending on the object of his research project, he sometimes selects the GF value within a meal’s PPG waveform of a 3-hours duration. Furthermore, the “primary range” of TIR is defined between 70 mg/dL and 180 mg/dL while a “secondary range” of TIR is defined between 70 mg/dL and 140 mg/dL. Of course, both the TIR’s and TAR’s percentages and their averaged values of secondary range (difference of 70 mg/dL) are smaller than the primary range results due to the secondary range’s narrower glucose range of 40 mg/dL (110-70 or 180-140). In summary, there are five noticeable findings from this study: (1) TIR: His TIR percentage (89%) and average TIR value (121 mg/dL) of the primary range, along with the TIR percentage (72%) and average TBR value (114 mg/dL) of the secondary range represent the majority of the data. This means that his type 2 diabetes (T2D) is quite well under control. (2) TBR: His TBR percentage (5%) and average TBR value (65 mg/dL) of the primary range, along with the same TBR percentage (5%) and the same average TBR value (65 mg/dL) of the secondary range contain rather small amounts. This means that his risk of having hypoglycemia (insulin shock) is relatively low.

A Novel Algorithmic Forex Trade and Trend Analysis Framework Based on Deep Predictive Coding Network Optimized with Reptile Search Algorithm

This paper proposed a short-term two-stage hybrid algorithmic framework for trade and trend analysis of the Forex market by augmenting the currency pair datasets with transformed attributes using a few technical indicators and statistical measures. In the first phase, an optimized deep predictive coding network (DPCN) based on a meta-heuristic reptile search algorithm (RSA) inspired by the intelligent hunting activities of the crocodiles is exploited to develop this RSA-DPCN predictive model. The proposed model has been compared with optimized versions of extreme learning machine (ELM) and functional link artificial neural network (FLANN) with genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE) along with the RSA optimizers. The performance of this model has been evaluated and validated through several statistical tests. In the second phase, the up and down trends are analyzed using the Higher Highs Higher Lows, and Lower Highs Lower Lows (HHs/HLs and LHs/LLs) trend analysis tool. Further, the observed trends are compared with the actual trends observed on the exchange price of real datasets. This study shows that the proposed RSA-DPCN model accurately predicts the exchange price. At the same time, it provides a well-structured platform to discern the directions of the market trends and thereby guides in finding the entry and exit points of the Forex market.

THE APPLICATION OF THE CUSTOMIZED SERVQUAL MODEL FOR CAREER GUIDANCE TRAINING: INDUSTRY 4.0 CHALLENGES

The importance of vocational guidance is growing, and the focus on modern tools enabling the development of competences such as flexibility, the ability to identify trends shaping the labour market and considering different scenarios of its development seem to be indispensable to survive in the world of work. The goal of the paper is to demonstrate a methodology and the outcomes of a research focused on the difference between the ideal characteristics and impressions of completed education by career counsellors in Poland. The research methods used are: the literature review, bibliometric analysis and the analysis and logical construction method. To diagnose the educational offerings the authors applied a modified SERVQUAL model. The observed gaps demonstrate the presence of significant discrepancies between the evaluation of the completed courses and the expectations of the respondents. Therefore, the expectations of those who took part in the survey about the quality of education in the field of vocational guidance are not fulfilled. The results of the analysis allow also to conclude that curricula only take little account of trend and scenario analysis tools specific to Industry 4.0; and this demonstrates a major challenge for including this curriculum content in the area of vocational guidance.

Evolution characteristics of temporal and spatial pattern of Russian economic differences since the 21st century.

Under the background of "the Belt and Road" and "the economic corridor of China, Mongolia and Russia" initiatives, it is of great significance to study the temporal and spatial economic pattern in the Russian Federation. Based on the economic development difference index, regional economic grade index, global trend analysis tool and spatial autocorrelation model, this paper analyzes the temporal and spatial pattern evolution characteristics of Russian economic differences from 2002 to 2020. The results are as following. First, although the economic imbalance among various federal subjects has been decreasing, the economic polarization has been still severe between the prosperous developed regions and the stagnant backward regions during 2002-2020. Russia's economy shows a trend of changing from significant positive correlation in strong agglomeration space to positive correlation in weak agglomeration space, and then to random distribution. Second, there has been great differences of the economic development among various federal subjects. The economic grade of the Russian federal subjects presents a significant spatial differentiation pattern. The Russian Federation's economic resources are concentrated in the first-class federal subject (Moscow City), second-class federal subjects (Tumen Region, Moscow Region and Saint-Petersburg city) and a few third-class federal subjects (Yamalo-Nenetsky Autonomous Area, Khanty-Mansiysky Autonomous Area, Republic of Tatarstan, Krasnodar Territory, Sverdlovsk Region, etc). Third, the Russian Federation's economy presents "High Core, Low Periphery", "High West, Low East" and "High south, Low north" spatial differentiation pattern. The economic hot regions coincide with the high-class economic regions, which are mainly distributed in the contiguous areas of Ural Federal District and Volga Federal District, as well as the Moscow City, Moscow Region, Saint-Petersburg city, Krasnodar Territory and Rostov Region. The economic cold regions coincide with the low-class economic regions, which are mainly located in the Far East Federal District, the east of Siberian Federal District, the north of North West Federal District and the south of North-Caucasian Federal District. Finally, we suggest the recommendation for policy makers in Russia. And we propose the future research ideas.

Forensic Accounting and Fraud Management in Nigeria

The study evaluated forensic accounting techniques on fraud management in the public sector MDAs in Nigeria. Arising from the rise in corruption in Nigeria evidenced in the Transparency International latest corruption perception index of Nigeria and the fact that the public sector constitutes a larger part of the economy in Nigeria, the study was undertaken to ascertain the operation-ability of forensic accounting techniques in public sector accounting departments. The study investigated Data mining, accounting ratios and trend analysis tools to detect or to prevent fraudulent activities in MDAs. Survey research design was adopted for the study. The study applying multiple regression analysis technique (OLS) revealed the adoption of forensic accounting tools (data mining, accounting ratios and trend analysis) will significantly enhance ability to detect and or prevent fraud in MDAs. Also revealed knowledge gap in the application of these preventive control techniques and the usefulness of trend analysis as a technique for detecting fraudulent practices in public service operations. It is thus recommended to develop the human capital of MDAs by making professional qualification and knowledge of information technology mandatory requirements for staff working in the accounts department and robust IT facilities in each MDA.

Meteorological Trend Analysis in Chandaka Wildlife Sanctuary, Odisha, India using Statistical Techniques

Globally, climate change has drawn a lot of attention. Depending on the area, the degree of the fluctuations or variability of the climatic factors changes. Therefore, it is crucial to evaluate climate influenced changes and recommend viable adaptation approaches by observing at temporal dynamics of various meteorological parameters in perspective climate change, mostly in the rain-fed agriculture dominant countries in the world. The current research describes the long-term patterns of meteorological variables such as precipitation, temperature, relative humidity, soil moisture, wind speed and solar radiation of the Chandaka Wildlife Sanctuary which is largely located in Cuttuck and Khordha Districts of the state of Odisha in India. The observed historical meteorological data from 1981 to 2021 were used in this study to assess the patterns. For that purpose, the current study examines short-term changes and long-term fluctuations in various meteorological parameters of Chandaka Wildlife Sanctuary. In this study, all of the meteorological data from the years 1981 to 2021 were evaluated. The issues were observed at and analyzed using statistical trend analysis tools like the Mann-Kendall (MK) analysis and Sen's slope estimation tests. According to a thorough review of the meteorological data for 41 years, the region between 1981 and 2021 experienced an increase in yearly precipitation, soil moisture and relative humidity pattern while seeing a decreasein wind speed, temperature and solar radiation pattern. Forty one years of data have been used to identify an annual long-term trend. The climatic parameters analyzed by this MK test show both decreasing and increasing patterns, proposing to major significant changes in the research area. In addition, this research into the area may disclose other aspects that will be supportive in controlling climatic parameters of the particular region.

Continuous Glucose Monitoring sensor glucose data analysis of Time in Range, Time Above Range, and Time Below Range for 4 annual mean values based on GH-Method: math-physical medicine (No. 507)

The author applies data pattern and curve trend analysis tools using his collected continuous glucose monitoring (CGM) sensor data over ~4-year period from 5/8/2018 to 9/5/2021. He further divides this long period into 4 annual sub-periods of 2018, 2019, 2020, and 2021 in order to investigate the annual differences of his glucose control situation. Special attention has been placed on applying the American Diabetes Association (ADA) 2020 Guidelines for Time In Range (TIR) % with TIR average glucose values between 70 mg/dL and 180 mg/dL, Time Above Range (TAR) % with TAR average glucose value above 180 mg/dL, and Time Below Range (TBR) % with TBR average glucose value below 70 mg/dL. With emphasis placed on TIR, instead of TAR or TBR, since TIR occupies the majority of his collected glucose data which indicates his T2D control situation. In summary, there are three key findings from this study: (1) TIR: Over the past 4 years, his TIR percentages are above 94% and the average TIR values are below 131 mg/dL, along with an average TBR percentages below 1.6% and an averaged TAR percentages below 4.9%. This means that his T2D is well under control with the majority (>94.9%) of glucoses within a reasonable and “acceptable” range. The risks probability of having hypoglycemia are below 1.6%, and his hyperglycemic risk probabilities are below 4.9%. (2) The lower TIR percentages and higher average eAG values over the period of 2018-2019 show that his T2D control is in better condition over the period of 2020-2021 (peaceful and routine lifestyle due to COVID quarantine) than the period of 2018-2019 (heavy travel lifestyle to attend many medical conferences). (3) This analysis only provides a “macro-view” of his T2D control; however, he needs to identify a “micro-view”. Both TIR and HbA1C provide the overview or the mean value of glucose situations. In other words, he needs additional research to gain a better understanding for the “shell of TIR”. This will be another topic in future research projects.

A Web Resource for Exploring the CORD-19 Dataset Using Root- and Rule-Based Phrases.

This short paper describes a web resource—the NIST CORD-19 Web Resource—for community explorations of the COVID-19 Open Research Dataset (CORD-19). The tools for exploration in the web resource make use of the NIST-developed Root- and Rule-based method, which exploits underlying linguistic structures to create terms that represent phrases in a corpus. The method allows for auto-suggesting-related terms to discover terms to refine the search of a COVID-19 heterogenous document base. The method also produces taxonomic structures in the target domain as well as providing semantic information about the relationships between terms. This term structure can serve as a basis for creating topic modeling and trend analysis tools. In this paper, we describe use of a novel search engine to demonstrate some of the capabilities above.

Pattern of GDP Growth Rate, Inflation, Interest Rate in Post Reform Period: A Comparative Analysis of India China and USA

Economic growth refers to an ability of an economy to increase its productive capacity through which it become more capable of producing additional units of goods and services. Economies all around are of great concern working on the new ways and techniques to promote the economic growth. The economic growth is also considered quite significant for economic policies; economies plan their economic policies accordingly. Macro variables play a very significant role in bringing economic growth to a country. It is said that major macro variables such as GDP, Inflation, Interest Rate, and Current Account Balance are interrelated. The objective of the study is to analyze the pattern of movement of fundamental variables in case of India, China, and USA. So this study emphasizes major macro variables of these countries in order to compare their economic growth. The time period is divided into two periods one is normal and another is recessionary period. Through trend analysis and basic econometric tools we will try to analyze the pattern of movement in fundamental variables during normal and recessionary period since post reform period. The hypothesis of the chapter is whether the pattern of movement in fundamental variables of the three countries is similar or varied. The findings says that Chinese economy is performing very well in terms of its fundamental variables while India is also performing well but USA economy is constant in terms of its fundamental variables although it is one of the developed and strongest economy of the world. So we cannot say that the fundamental variables of these three economies are showing similar patterns.

Application of Analytical Hierarchical Process (AHP) in Development of Suitability Model for Rice Production in Taraba State

This research was aim at applying Multi-Criteria Decision Making (MCDM) in Agro-Climatic Zoning of Taraba State for rice Production. Climatic variables, Rice Yield, Digital Elevation Model (DEM), Land Sat 8 (OLI) and Soil Texture map were the data used. Climatic data of the state were analyzed over time and Space using trend and spatial analysis tools in excel and Arc GIS respectively, while correlation and stepwise regression analysis between rice yield and the climatic variables were analyzed in SPSS. Mean temperature, August and September rainfalls were identified to be the critical Climatic factors affecting the growth and yield of rice in the State. The highly suitable cover places such as; Lisasam, Takum, Donga, Wukari, Mutum Biyu and Bali while the suitable area occupy places like Serti, Lau, Sunkani, Jalingo and Lankaviri. Suitability map produced with NDVI showed that the highly suitable area for Rice cultivation reduced from 31.93% to 28.76%. In regards to this findings, cultivation of rice should be encourage in Highly Suitable and Suitable zones of the State while cultivation of alternative crops other than rice in not suitable area is very important in reducing the risk of crop failure. In addition, application of Multi Criteria Decision Making (MCDM) a Remote Sensing and GIS tool and NDVI plays a significant role in Agro-climatic suitability zoning, as such, the tools are recommended in Agro-climatic research.

Pengaruh inflasi dan jumlah uang beredar terhadap nilai tukar rupiah dengan pendekatan model struktural VAR

The purpose of this study are, firstly to analyze exchange rate trends of rupiah, centtral bank policy rates, inflation and money supply in Indonesia from January 2019 to December 2019. Secondly, to analyzes the effect of central bank policy rate, inflation and the money supply to the rupiah exchange rate in January 2013 – Desember 2018. The method used in this research are descriptive and quantitative analysis with trend analysis tools and multiple linier regression VAR models with the Ordinary Least Square (OLS). The results of the study found that, the first trend data from the rupiah exchange rate variable of January 2019 period – December 2019 of IDR 15.145 US$, the central bank’s policy interest rate was 4.5 percent, inflation was 2.15 percent and the money supply was an average of Rp.5.966.9112,17 billion. Secondly, from the processed data it was found that central bank policy rates and the money supply has a positive effect on the rupiah exchange rate of January 2013 period – December 2018. While the inflation variable has a negative impact on the rupiah exchange rate of January 2013 period – December 2018. Keywords : Rupiah exchange rate, Central bank policy interest rate, Money supply

The Use of Earned Value Management As a Trend Analysis Tool in UK Construction Sector

This paper discussed the use of earned value management as an analytical tool in construction sector to increase project success rate with the aim of illustrating how EVM is used on previous project and quantify the impact in construction project. In this paper, we tried to evaluate this method used in project management by using three case studies that shows how this is implemented. These case studies are documented with reports, graphs, analyses and comments. EVM contribution to the success of these case studies by identifying the main problems and solution those results into the project finishing on time and on budget. Overall, the paper summarizes how EVM has helped construction industries see the usefulness of this tool in given a clearer insight to the project by showing the project status in terms of cost and time and forecasting when the project would be finished.

Development of a Facebook Crawler for Opinion Trend Monitoring and Analysis Purposes: Case Study of Government Service Delivery in Dwesa

service providers it is important to know what the public thinks or requires. Having such knowledge can help in decision making and future planning. In nowadays there is very high usage of Social Networking Sites (SNSs) and blogs where people share their views, opinions, and thoughts. If service providers can keep track of such views, opinions or thoughts with regard to the services they provide, they can better their understanding about the public or clients' needs and improve the provision of relevant services. This paper presents a system prototype for performing trend analysis on Facebook. The proposed system crawl Facebook, indexes the data and provides user interface where end users can search and see the trend of topic of their choice. The main objective of this paper is to propose a framework that can contribute in the improvement of the way government official and normal citizens communicate in regard with service delivery in rural areas. The premise in this paper is that if the government can keep track of the citizen's opinions and thoughts with regards to service delivery, it can help improve the delivery of such services. This research and the implementation of the trend analysis tool is undertaken in the context of the Siyakhula Living Lab (SLL), an Information and Communication Technologies for development (ICTD) intervention for Dwesa marginalized community located in the Eastern Cape province of South Africa.

A new trend analysis for seasonal time series with consideration of data dependence

Summary Trend analysis has been an important tool in assessing hydrological process. However, statistical approaches employed for trend analysis frequently assume independence in hydrological time series. To satisfy the independence assumption, the hydrological series of interest are usually summarized to large scale data (e.g. annual) for long-term trend. To assess intra-annual variability, the hydrological series are summarized to several periods within a year (e.g. season or month) and then analyzed separately for each period over different years (e.g. each month over different years). Unfortunately, for those seasonal and monthly data, the trend analysis must be conducted separately for individual periods in order to avoid data dependence. However, the setting of periodic models cannot guarantee the smoothness in model coefficients from period to period (e.g. month to month). In this paper, we develop a trend analysis tool by including a period component in the method. By doing this, the data dependence and seasonality will not be issues but become advantages as information gain for each period. The proposed method treats the change in hydrological series as the interaction between long-term trend and seasonal variation. The functional coefficient model with a periodic component is used for model development. Unlike the traditional functional coefficient models which extend the threshold regression model, our functional coefficient model with periodic components enjoys smoothing changes from year to year. As case studies, the models are applied to Australian streamflows in three typical climate conditions.

Patterns of Agricultural Growth and Overall growth of Ugandan Economy

This study aimed at establishing simple stylized facts on relationships between the share of agriculture and its subsectors in GDP and GDP per capita in Uganda. The study utilized both trend and regression analysis tools to achieve the study objective. Previous studies give evidence on what has come to be a stylized fact , that the share of agriculture in GPD falls as the GDP per capita of an economy increases. Our findings by both the trend and regression analysis confirm this stylized fact. However, when agriculture is disaggregated, the pattern that emerges is not consistent with previous studies. Whereas, the overall agriculture and the subsectors of agriculture such as food crops, livestock and forestry share in GDP falls as GDP per capita rises the fishing sector share in GDP does not exhibit a significant relationship with per capita income. The findings also show that whereas the share of non-monetary agriculture, non-monetary food crops, non-and monetary livestock share in GDP exhibit a negative relationship with GDP per capita income, the share in GDP of monetary agriculture, monetary food crops, cash crops, monetary and non monetary forestry and fishing exhibit no significant relationship with GDP per capita. Key words: Performance, Ugandan economy GDP, per capita, agriculture sector.

The development of a time trend analysis tool for GIS and its application in the assessment of Nash Bank, South Wales

Incorporating a temporal function (i.e. to analyse data over time) into the spatial environment of GIS has been developed and applied in the assessment of the evolution of Nash Bank, South Wales. A stringent programme of monitoring, including annual bathymetric surveys of the bank, is carried out as part of the requirements of aggregate dredging and provides suitable data to analyse changes in bank levels over time. Traditionally GIS has been used to assess the evolution of such coastal landforms by creating a digital terrain model (DTM) for each of the bathymetric datasets and then performing a simple calculation whereby one DTM is subtracted from an earlier one. However, a simple difference in levels between any two snapshots in time can be misleading when trying to evaluate long-term rates of change. The new GIS tool has been developed that calculates such rates (i.e. the time trend) by incorporating a linear regression formula. The results are then plotted out by the tool into GIS as a DTM, in which each individual data cell represents a rate of change (time trend) at that particular location, allowing a clear temporal analysis to be presented for the whole area.

Exploring the IBIS data library contents: Tools for data visualisation, (pre-) processing and screening

During the IBIS project a high-quality data library of continuous and intermittent physiological signals and variables from patients during intensive care and surgery has been collected. To facilitate exploration of the full content of this data library a data browser was developed, which offers a flexible graphical display of the collection of multivariate data. To supplement the functionality of the display of the ‘raw’ data, a set of screening and pre-processing tools has been developed. A separate trend analysis tool offers a convenient overview of an entire recording focusing on the slow changes in the general state of the patient and the interaction between different physiological subsystems seen from a long-term perspective. A frequency analysis tool for processing the electroencephalography (EEG) signals has been integrated in the data browser to facilitate a quick screening of the cerebral function. The data library is the foundation of the development and validation of biosignal interpretation methods. This process can potentially be more productive using the described tool for algorithm prototyping based on a graphical network specifying the interaction between data processing primitives.