Biggest Value Research Articles

DeepFeat: Robust Large-Scale Multi-Features Outdoor Localization in LTE Networks Using Deep Learning

In today’s Telecom market, Telecom operators find a big value in introducing valuable services to users based on their location, both for emergency and ordinary situations. This drives the research for outdoor localization using different wireless technologies. Long Term Evolution (LTE) is the dominant wireless technology for outdoor cellular networks. This paper introduces DeepFeat: A deep-learning-based framework for outdoor localization using a rich features set in LTE networks. DeepFeat works on the mobile operator side, and it leverages many mobile network features and other metrics to achieve high localization accuracy. In order to reduce computation and complexity, we introduce a feature selection module to choose the most appropriate features as inputs to the deep learning model. This module reduces the computation and complexity by around 20.6% while enhancing the system’s accuracy. The feature selection module uses correlation and Chi-squared algorithms to reduce the feature set to 12 inputs only regardless of the area size. In order to enhance the accuracy of DeepFeat, a One-to-Many augmenter is introduced to extend the dataset and improve the system’s overall performance. The results show the impact of the proper features selection adopted by DeepFeat on the system’s performance. DeepFeat achieved median localization accuracy of 13.179m in an outdoor environment in a mid-scale area of 6.27Km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . In a large-scale area of 45Km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the median localization accuracy is 13.7m. DeepFeat was compared to other state-of-the-art deep-learning-based localization systems that leverage a small number of features. We show that using DeepFeat’s carefully selected features set enhances the localization accuracy compared to the state-of-the-art systems by at least 286%.

Theoretical Calculations of pKa Values for Substituted Carboxylic Acid

Six different methods of determination have been used for studying ten derivatives of carboxylic compounds. Semi-empirical (AM1 and PM3), Hartree Fock (HF/STO-3G and HF/3-21G), and Density Function Theory (DFT/STO-3G and DFT/6-31G) were employed to calculate many physical theoretical parameters. The calculated data were correlated with experimental values of pKa using different regression(enter, stepwise and simple regression). Depending on the Fisher values, (HF/STO-3G) was shown as the best method for predicted of the pKa data compare to the (PM3) method using enter method. While (HF/3-21G)method has a big value of fisher compared with(PM3) using (stepwise) and (simple) methods. So, Multiple linear regression was performed to obtain the best prediction values using (enter) compare with (stepwise), and the two methods are the best compared with simple regression.

UNDERSTANDING BIG DATA-FAIR VALUE MEASUREMENT MODEL OF BIOLOGICAL ASSETS

This research establishes a Big Data-Fair Value Measurement Model of Biological Assets using a Smart Farming Approach. The aim of the study is to gather literature knowledge about the judgment of biological assets. The use of big data and innovative farming in the agricultural sector is relatively new in Malaysia, making people wonder about its effectiveness, whether positive or negative. However, determining fair value can be a daunting task due to the existence of personal biological properties and the variety of specimens (offspring), classes, and conditions. Agricultural sectors need to be more emphasised by many parties as the increases in cost production is not a trivial matter that can be ignored. There have been pressures from foreign countries such as Thailand, Vietnam, and Indonesia in the agricultural sector. Malaysia faces one major challenge: the cost of production, including wages and inputs, is relatively higher. (Rozhan 2019). Agricultural accounting is a minor standard, but it has a broad scope and a significant impact on agricultural businesses based on the accounting perspective, the MFRS141/IAS 41. The standard improves the transparency of the cost to replace capital (by allowing for depreciation and amortisation) and better reflects the productive lifespan of assets in agricultural operations. However, the application of MFRS 141 Agriculture is still relatively new in Malaysia, and a thorough examination of the literature indicates several gaps and deficiencies. This literature review is vital to support the study on Big Data-Fair Value Measurement Model of Biological Assets as the agricultural sector's involvement was recently popular. It might also offer some good ideas for handling problems involving the fair value measurement. Future studies will help the Ministry of Agriculture and Food Industries, agriculture sector workers, in terms of practical perspective. Therefore, the future result of the study suggests an improvement within the agriculture sector related to the treatment in their fair values, issues, and strategies.

Research on Service Innovation of Financial Data based on Cloud Computing in Big Data Era

With the increasing penetration of the Internet into people's lives, the financial market in the era of big data directly affects the asymmetric information mode between the supply and demand sides, and on this basis, it plays a positive role in guiding the subsequent optimization of financial market services, ensuring social fairness and reducing the exclusion of financial products. Big data finance under the Internet has narrowed the distance between supply and demand, subverted the problem of information asymmetry between the two sides, and injected new innovative means to alleviate financial exclusion, promote social equity and optimize financial services. In order to support the development of the real economy and enhance the core competitiveness of the industry, the process of data value chain has been continuously extended horizontally and vertically, but the data value chain of financial enterprises has been extended. In this paper, starting from the characteristics of the big data era, taking the carrier of value extension as the research goal, the big data value chain model of financial enterprises is constructed based on cloud computing technology, and the service innovation of China's financial data in the big data era is discussed.

Heterogeneous Analysis of the Nexus between Big Data Analytics and Value Co-Creation: Insight from Selected Service Businesses in Ghana

The study examines big datas role analytics ininterfirm value co-creation in selected service businesses in Ghana by focusing specifically on the heterogenous big data characteristics. This is in response to the ongoing debate on value co-creation and big data nexus. Using data from 61 purposively sampled service businesses in Accra-Ghana, the structural equation model provides that; big data analytics positively influences interfirm value co-creation in the selected businesses. Further, aside from big data volume, all the other big data characteristics (velocity, veracity, value, and variety) also individually influence value co-creation. Therefore, this challenges businesses of all sizes to invest in the application of big data for strategic decisions like value co-creation. Again, although businesses should be willing to collaborate with others, big data teams should be fully equipped for optimal analytics.

STRATEGI DIGITAL BRANDING UNTUK MENINGKATKAN PENJUALAN UMKM INDONESIA

This is the time for us to see the positive side caused by pandemic. Even though not everybody agrees to this, the pandemic going on not only in Indonesia but also in all over the world has given us a chance for ‘adaptation’ over changes in business. Nowadays, business concept is not only affected by markets, companies, competitors but also by changes. Every individual, even a big company must acknowledge this. In order to maintain the side of people’s ‘economy’, various studies reviewing alternatives for good marketing strategies have been carried out. These studies are especially aimed at Small and Medium Enterprises (SMEs). This is because SMEs have been the part of creative economy. Based on these circumstances, the researcher was encouraged to study which strategy of digital branding dominantly carried out by the SME players. This research applied factor analysis to find out the basic attribute grounding SME players to survive their businesses, which were initiated either before or after pandemic. The method used was non-probability sampling. Here the questionnaires were distributed in order to find answers from five determined spots. There were 169 respondents as samples in this research. In the pre-test, before questionnaires distributed, there were at least 9 attributes used as references for the main players of SMEs in applying digital branding. Results of factor analysis test showed that there were at least two main factors developed. In these two factors, it is agreed that strategy of Search Engine Optimization was the most ideal to apply in order to survive their business. This is because it has big dominant value, which was 0.823 (82% for first group) and 0.790 (79% for the second group).

A spiral-like method to place in the space (and interact with) too many values.

Modern information systems have to support the user in managing, understanding and interacting with, more and more data. Visualization could help users comprehend information more easily and reach conclusions in relative shorter time. However, the bigger the data is, the harder the problem of visualizing it becomes. In this paper we focus on the problem of placing a set of values in the 2D (or 3D) space. We present a novel family of algorithms that produces spiral-like layouts where the biggest values are placed in the centre of the spiral and the smaller ones in the peripheral area, while respecting the relative sizes. The derived layout is suitable not only for the visualization of medium-sized collections of values, but also for collections of values whose sizes follow power-law distribution because it makes evident the bigger values (and their relative size) and it does not leave empty spaces in the peripheral area which is occupied by the majority of the values which are small. Therefore, the produced drawings are both informative and compact. The algorithm has linear time complexity (assuming the values are sorted), very limited main memory requirements, and produces drawings of bounded space, making it appropriate for interactive visualizations, and visual interfaces in general. We showcase the application of the algorithms in various domains and interactive interfaces.

Applying text mining to identify relevant literature in food science: Cold denaturation as a case study.

In a research environment characterized by the five V's of big data, volume, velocity, variety, value, and veracity, the need to develop tools that quickly screen a large number of publications into relevant work is an increasing area of concern, and the data-rich food industry is no exception. Here, a combination of latent Dirichlet allocation and food keyword searches were employed to analyze and filter a dataset of 6102 publications about cold denaturation. After using the Python toolkit generated in this work, the approach yielded 22 topics that provide background and insight on the direction of research in this field, as well as identified the publications in this dataset which are most pertinent to the food industry with precision and recall of 0.419 and 0.949, respectively. Precision is related to the relevance of a paper in the filtered dataset and the recall represents papers which were not identified in the screening method. Lastly, gaps in the literature based on keyword trends are identified to improve the knowledge base of cold denaturation as it relates to the food industry. This approach is generalizable to any similarly organized dataset, and the code is available upon request. Practical Application: A common problem in research is that when you are an expert in one field, learning about another field is difficult, because you may lack the vocabulary and background needed to read cutting edge literature from a new discipline. The Python toolkit developed in this research can be applied by any researcher that is new to a field to identify what the key literature is, what topics they should familiarize themselves with, and what the current trends are in the field. Using this structure, researchers can greatly speed up how they identify new areas to research and find new projects.

Additive role of dynamic subtraction MRI in assessment of unresolved HCC post-radiofrequency ablation

BackgroundMalignant Hepatocellular carcinoma (HCC) is one amongst the foremost widespread cancers within the world. Radiofrequency ablation (RFA) is that the most generally used substitute tool for hepatic carcinoma treatment. Monitoring tumoral response to loco-regional therapy is a vital mission in oncological imaging. Dynamic contrast enhanced MR and recently added subtraction imaging technique improve assessment of the ablated hepatic focal lesions. The aim of this study is that the evaluation of the role of Subtraction MRI within the detection of recurrent or residual tumoral viability after RF ablation.ResultsFifty patients were conducted during this retrospective study, all underwent RFA for 76 hepatic focal lesions and underwent Dynamic MRI study 1 month after ablation. Subtraction imaging was then performed. MRI images were interpreted by two readers who are experienced in hepatic imaging. The primary reader interpreted the standard Dynamic MRI and was blinded to the subtraction sequences; the second reader interpreted both Dynamic and Subtraction MRI images. the primary reader detected 49 resolved cases by dynamic MRI, while the second reader detected residual activity in 6 cases out of 49 via subtraction dynamic MRI (added value). The second reader agreed with first reader in 43 cases (agreement).The first reader detected 27 residual cases by dynamic MRI. The second reader disagreed with first reader in 11 cases appeared resolved out of 27 via subtraction dynamic MRI (added value). The second reader agreed with first reader in residual activity in 16 cases (agreement).The statistical analysis of those results revealed a big additive value of the subtraction imaging to the dynamic MRI (P < 0.001) with moderate degree of agreement between the 2 diagnostic tools (Kappa value = 0.491). This implies that Subtraction MRI significantly improves the reader confidence level within the assessment of treatment response following loco-regional therapies for HCC.ConclusionDynamic Subtraction MRI is a powerful detector for real enhancement in treated HCC lesions after radiofrequency ablation and hence increasing the degree of readers’ confidence and accuracy of treated lesions in follow-up studies. So it's recommended to feature this powerful tool as a routine to any or all Dynamic MRI studies of the Liver.

Pengenalan Strategi Digital Branding Untuk Meningkatkan Penjualan Umkm Pada Komunitas Umkm Desa Gelam Jaya, Kabupaten Tangerang

This is the time for us to see the positive side caused by pandemic. Even though not everybody agrees to this, the pandemic going on not only in Indonesia but also in all over the world has given us a chance for ‘adaptation’ over changes in business. Nowadays, business concept is not only affected by markets, companies, competitors but also by changes. Every individual, even a big company must acknowledge this. In order to maintain the side of people’s ‘economy’, various studies reviewing alternatives for good marketing strategies have been carried out. These studies are especially aimed at Small and Medium Enterprises (SMEs). This is because SMEs have been the part of creative economy. Based on these circumstances, the researcher was encouraged to study which strategy of digital branding dominantly carried out by the SME players. This research applied factor analysis to find out the basic attribute grounding SME players to survive their businesses, which were initiated either before or after pandemic. The method used was non-probability sampling. Here the questionnaires were distributed in order to find answers from five determined spots. There were 169 respondents as samples in this research. In the pre-test, before questionnaires distributed, there were at least 9 attributes used as references for the main players of SMEs in applying digital branding. Results of factor analysis test showed that there were at least two main factors developed. In these two factors, it is agreed that strategy of Search Engine Optimization was the most ideal to apply in order to survive their business. This is because it has big dominant value, which was 0.823 (82% for first group) and 0.790 (79% for the second group).

Effect of density dependence on coinfection dynamics

In this paper we develop a compartmental model of SIR type (the abbreviation refers to the number of Susceptible, Infected and Recovered people) that models the population dynamics of two diseases that can coinfect. We discuss how the underlying dynamics depends on the carrying capacity K: from a simple dynamics to a more complex. This can also help in understanding the appearance of more complicated dynamics, for example, chaos and periodic oscillations, for large values of K. It is also presented that pathogens can invade in population and their invasion depends on the carrying capacity K which shows that the progression of disease in population depends on carrying capacity. More specifically, we establish all possible scenarios (the so-called transition diagrams) describing an evolution of an (always unique) locally stable equilibrium state (with only non-negative compartments) for fixed fundamental parameters (density independent transmission and vital rates) as a function of the carrying capacity K. An important implication of our results is the following important observation. Note that one can regard the value of K as the natural ‘size’ (the capacity) of a habitat. From this point of view, an isolation of individuals (the strategy which showed its efficiency for COVID-19 in various countries) into smaller resp. larger groups can be modelled by smaller resp. bigger values of K. Then we conclude that the infection dynamics becomes more complex for larger groups, as it fairly maybe expected for values of the reproduction number R_0approx 1. We show even more, that for the values R_0>1 there are several (in fact four different) distinguished scenarios where the infection complexity (the number of nonzero infected classes) arises with growing K. Our approach is based on a bifurcation analysis which allows to generalize considerably the previous Lotka-Volterra model considered previously in Ghersheen et al. (Math Meth Appl Sci 42(8), 2019).

The value of open data government: a quality assessment approach

Data quality involves a set of characteristics, values, and expressions that are built iteratively. Open government data (OGD) shares the qualities of Big Data regarding volume, speed, accuracy, and value, and the purpose of achieving stakeholders’ reuse stands out. This study uses a bibliographic review to identify the relationships among big data, open data, data quality, and value. We conclude that OGD, a recent trend, encourages collaboration and citizen participation and enables reusing data to pursue public and private innovation. Ensuring data quality makes it possible to obtain value from its reuse and generate Economic Value, Commercial Value, Social Value, and Public Value. Consumers require a solid basis of trust before using public information, which requires a data quality assurance process that strengthens and intensifies the inherent value of the data and activates its potential in different contexts.

Bias voltage effect on impedance, modulus and dielectric spectroscopies of HfO2-interlayered Si-based Schottky diodes at room temperature

In this study, Al/HfO2/p-Si metal-insulator-semiconductor (MIS) Schottky diode was fabricated by atomic layer deposition (ALD) technique with an adjusted HfO2 interlayer thickness of 3.3 nm. Using (I, V), (Z, θ) and (C, G) experimental data sets, the electric and dielectric properties of the fabricated diode were investigated in 1 kHz–10 MHz frequency range at different applied bias voltages at room temperature through complex functions like impedance, modulus, conductivity and dielectric. From the DC current-voltage (I–V) measurements, the ideality factor and the barrier height of the diode were estimated at room temperature as 2.22 and 0.86 eV, respectively. AC measurement results demonstrated the presence of two different polarization mechanisms (interfacial and orientational) in the investigated frequency range. The results also clearly showed that three relaxation phenomena exist within the diode bulk structure, and that both relaxation and conduction mechanisms are activated by the applied bias voltage. One of the relaxations was the Warburg relaxation spotted in the low frequency region in two different forms (semi-infinite Warburg in impedance Nyquist plots and finite-space Warburg in dielectric Nyquist plots) and both were explained by the slow diffusion of Al3+, O2− and Hf4+ ions across the interface layer. Equivalent circuit impedance fit analysis showed that the fabricated diode has a good MIS structure due to the demonstrated high resistivity and low-leakage of the interfacial HfO2 layer. The big values of the dielectric loss tangent (8.03 at 500 kHz and +2 V) as compared to the dielectric constant (0.13 at 500 kHz and +2 V) at room temperature and the independence of dielectric constant on temperature suggests the appropriate usage of the fabricated diode in thermal heating applications. The estimated four major parameters (ideality factor, barrier height, dielectric constant and dielectric loss tangent) were compared with other literature results based on different growth parameters and tabulated in conclusion.

A Unified Scheme for Distance Metric Learning and Clustering via Rank-Reduced Regression

Distance metric learning aims to learn a positive semidefinite matrix such that similar samples are preserved with small distances while dissimilar ones are mapped with big values above a predefined margin. It can facilitate to improve the performance of certain learning tasks. In this article, distance metric learning and clustering are integrated into an unified framework via rank-reduced regression. First, distance metric learning is proved to be consistent with rank-reduced regression, which provides a new perspective to learn structured regularization matrices. Second, orthogonal and non-negative rank-reduced regression problems are addressed individually for clustering, and the corresponding algorithms with proved convergence are proposed. Finally, both distance metric learning and clustering are addressed simultaneously in the problem formulation, which may trigger some new insights for learning an effective clustering oriented low-dimensional embedding. To show the superior performance of the proposed method, we compare it with several state-of-the-art clustering approaches. And, extensive experiments on the test datasets demonstrate the superiority of the proposed method.

Research on the Transformation and Upgrading Path of Traditional Industries Driven by Big Data from the Perspective of Big Data Value Chain

Due to the rapid development of digital technology, digital form has become the development direction of various industries. As the main development factor of the current digital economy, big data can effectively drive traditional industries and new transformation and upgrading, bring positive influence to the development of various traditional industries and industries, and effectively solve the problem of high cost and low harvest in traditional industries. Therefore, through the research on the basic theoretical knowledge of big data and the exploration of its internal value connotation from the perspective of the value chain of big data, and the value creativity of big data can be used to complete the transformation and upgrading of the traditional industrial nature. In addition, the three elements of the big data value chain, including data quality, innovative thinking and data analysis ability, provide the ways and means for the transformation of traditional industries, and then put forward relevant policy suggestions for the transform and upgrade the nature of traditional industries.

Big Data Value Chain: Multiple Perspectives for the Built Environment

Current climate change threats and increasing CO2 emissions, especially from the building stock, represent a context where action is required. It is necessary to provide efficient manners to manage energy demand in buildings and contribute to a decarbonised future. By combining new technologies, such as artificial intelligence, Internet of things, blockchain, and the exploitation of big data towards solving real life problems, the way could be paved towards smart and energy-aware buildings. In this context, the aim of this paper is to present a critical review and an in-detail definition of the big data value chain for the built environment in Europe, covering multiple needs and perspectives: “policy”, “technology” and “business”, in order to explore the main challenges and opportunities in this area.

Analysis of the Risk of Profit Loss in Papaya Farming Affected by Yellow Mosaic Disease

Profit loss is a phenomenon caused by the loss of most of the harvest resulting in operating costs greater than the revenue earned. This phenomenon deserves to be analyzed the risk of losses that will be obtained due to pests and plant diseases. So that in this study an analysis of the risk of Profit loss due to yellow mosaic disease on papaya calina was carried out. This research was conducted in October 2020 in Bengkulu Province on 31 Calina Papaya farmers. The location selection was carried out purposively based on the existence of the Calina papaya garden. Meanwhile, the selection of respondents was carried out using the Snowball sampling method in several districts in Bengkulu Province. Data analysis was carried out to determine the Profit loss. Based on the results of the analysis, it was found that there were differences in the benefits of papaya calina which were attacked by the Yellow Virus Mosaic and those that were not attacked by the Yellow Virus Mosaic. Profit loss for a year is Rp 9,135,203,-. This value is a big value, so farmers must handle this disease better.

Ефективність сільського господарства України: порівняльний аналіз в розрізі країн

Abstract. Introduction. Agriculture plays prominent role to supply people with food and industry with raw. The development of this branch depends on as economic conjuncture as nature conditions. Ukraine agriculture have developed in two directions during the period of 1991-2018. After several years of declining this branch has started reviving since 2009. The question is how successful this process is flowing. Various investigations cover analysis of dynamics, structure, correlations between indicators, forecasting and juxtaposing with other economic branches. Studying experience of other economies that had downs, but then accumulated their strengths and made economical leap, is the example for own start in development. What caused the growth and what made countries prosperous? This experience must be studied and implemented by scientists, government, and farmers. Most nowadays successful countries started from revision of existing styles of agricultural management and farm holding. They initiated reforms and adopted laws that had to support development of farms. Some of countries, that have been under influence of Soviet Union's style of management, being independent now are in the category of countries with middle or high world level of income. In contrary, Ukraine during almost thirty years of independence is fighting problems in economic development caused by negative factors including crises. To study features of countries’ growth and eliminate influence of inflation or incomparable indicators on results of analysis it is reasonable to investigate the same indicators for the similar period in determined currency. This article presents comparison results made for Ukraine Poland, Belarus, Moldova, Estonia, Lithuania, Latvia despite their size and political preferences. Information for analysis used in this exploration is on the World Bank official site. Data cover the period of 1995-2019 years. Purpose. The main aim of this article is to compare indicators of agriculture development in Ukraine with other countries in order to find how successful and sufficient economic efforts of Ukraine are to raise agriculture sector on the higher level of development. Results. Conducted analysis revealed that other countries compared with Ukraine get bigger value added per worker or per unit of agriculture land. Moreover, they not only feed own country, but also sell their production abroad. Conclusions. Ukraine has the biggest soils squares to plant crops, vegetable, fruit, but it gets the least amount of profit from land usage. Ukraine has positive tendency in agriculture development, but as comparison with other countries proved the existing way of land using or cultivation, farm holding, and agriculture management is insufficient to become a prosperous country. Crop and livestock production need to be investigated deeper.

Experimental &amp; FEM Analysis of Orthodontic Mini-Implant Design on Primary Stability

The main objective of this research is to establish a connection between orthodontic mini-implant design, pull-out force and primary stability by comparing two commercial mini-implants or temporary anchorage devices, Tomas®-pin and Perfect Anchor. Mini-implant geometric analysis and quantification of bone characteristics are performed, whereupon experimental in vitro pull-out test is conducted. With the use of the CATIA (Computer Aided Three-dimensional Interactive Application) CAD (Computer Aided Design)/CAM (Computer Aided Manufacturing)/CAE (Computer Aided Engineering) system, 3D (Three-dimensional) geometric models of mini-implants and bone segments are created. Afterwards, those same models are imported into Abaqus software, where finite element models are generated with a special focus on material properties, boundary conditions and interactions. FEM (Finite Element Method) analysis is used to simulate the pull-out test. Then, the results of the structural analysis are compared with the experimental results. The FEM analysis results contain information about maximum stresses on implant–bone system caused due to the pull-out force. It is determined that the core diameter of a screw thread and conicity are the main factors of the mini-implant design that have a direct impact on primary stability. Additionally, stresses generated on the Tomas®-pin model are lower than stresses on Perfect Anchor, even though Tomas®-pin endures greater pull-out forces, the implant system with implemented Tomas®-pin still represents a more stressed system due to the uniform distribution of stresses with bigger values.

UNDERSTANDING CUSTOMER ACCEPTANCE TO FINANCIAL TECHNOLOGY; STUDY IN INDONESIA

In the Era of Digital 4.0, technology is of undeniable importance to any industry, including banking and finance. The disruption of technology and economic crisis has brought us the innovation of financial technology which is now mushrooming throughout the world. Financial Technology is an instrumental tool for financial inclusion thus has a big potential value in countries such as Indonesia. However, the acceptance of this new way of financial alternative still leaves a huge area for investigation. Especially in the acceptance of this technology as an alternative to conventional way of doing financial investment.The article is trying to investigate the acceptance of the financial technology sector to customers and the intention to use it in the future. The research found that the minimal effort and the availability of resources that facilitate contribute greatly to the acceptance of financial technology to the users. Furthermore, the result implies that social factors, hedonic motivation and habits have no significant effect on the intention of adapting this new way of doing financial activities.