Big Dimensions Research Articles

Debugging missing answers for spark queries over nested data with breadcrumb

We present Breadcrumb, a system that aids developers in debugging queries through query-based explanations for missing answers. Given as input a query and an expected, but missing, query result, Breadcrumb identifies operators in the input query that are responsible for the failure to derive the missing answer. These operators form explanations that guide developers who can then focus their debugging efforts on fixing these parts of the query. Breadcrumb is implemented on top of Apache Spark. Our approach is the first that scales to big data dimensions and is capable of finding explanations for common errors in queries over nested and de-normalized data, e.g., errors based on misinterpreting schema semantics.

Survey on the Production of Traditional Bioenergy in the Democratic Republic of the Congo: The Case Study of Kwilu Province

The present research has been carried out in three different groupings, namely Mudikwiti, Tanganga and Nkata in Kwilu province, in the Democratic Republic of the Congo. 165 coalmen from eighteen villages have been considered as the sample used in this work. They are selected from all social strata, and their ages vary from 18 to 30 years old and from 44 to 56 years old. They have made 21,899 ovens, among which there were 12, 287 ovens of small dimensions, that is, 1 m x 6 m x 3 m, and 9,612 ovens of big dimensions: 6 m x 20 m x 3 m. They have cut 196,694 trees of different species to fill in the two kinds of ovens, say 99,984 trees for filling in small ovens and 96,710 trees to fill in big ovens. On the whole, they have produced 852,708 sacks of charcoal per year. The Nkata grouping, with its 11 villages, has produced 129,600 sacks of 45 kilograms, divided as follows: 14,400 sacks from the small dimension ovens and 115, 200 sacks from the big dimension ovens.

Numerical modeling of the electron beam welding for port stub of CFETR vacuum vessel

The port stubs are larger welding parts of stainless steel plate, featuring with complicated structure and big overall dimensions contain complex local flanging shape and demand high forming quality. It is very important to forecast the welding stress and control the welding residual deformation exactly to ensure the safe reliability of the structure. In this paper, the welding distortions of port stub were predicted by inherent strain method and the welding sequence and clamping design were optimized. Three possible welding constraints and three welding sequence schemes of the port stub were provided within the actual processing condition, weld distortions were studied. Finally, the smallest welding deformation was under welding constraints 3, welding sequence 1, and the maximum welding deformation was 2.968 mm. The simulations were used to guide the manufacture of the final sequence and clamping design of the port stubs.

Changes in the Market of Precious Wood: A Case Study of Submission System in Poland

A timber market occupies a very particular position within the economic reality. Trading of commodities such as precious timber is, indeed, strongly conditioned by the carrying capacity and the silvicultural potential of the forest ecosystem. Timber markets in Poland are characterized by a controlling position of the State Forests, and one of the possible forms of wood sale is the system of submission. A submission usually implies that small quantities of wood with unusual features are being offered to a specific group of customers. The paper presents the sale results and prices of veneer wood commercialized in submission systems and in other forms of timber sale in the territory of Krosno during the years 2000−2019. It is one of the oldest submission markets in Poland, where the most expensive log ever in Poland was sold (13,000 USD/log—close to 7000 USD/m3). The Regional Directorate of State Forest (RDSF) of Krosno is located in the south-eastern part of Poland and manages a forest area of approximately 400,000 hectares. Annual timber harvesting amounts to 2 million m3, of which less than 2000 m3 annually is allocated to the submissions. The data cover a 20-year continuous time series and allow tracing changes in the wood volume offered to the market, the species population structure, and price trends for individual species. The data are being discussed against the background of the economic situation and in relation to the average prices obtained from other methods of sale. Beech was the most sold, but the demands for oak and sycamore appeared to be particularly high during the period of observation. The unity prices can be very variable even for wood from the same species, especially for sycamore. The prices are generally demand-driven and show strong influences from furniture industries and fashion. A rising demand for high quality timber and logs of big dimensions has been noticed. The submission system results in substantial economic benefits for the forest management and the region as a whole.

Exploring big data traits and data quality dimensions for big data analytics application using partial least squares structural equation modelling

The popularity of big data analytics (BDA) has boosted the interest of organisations into exploiting their large scale data. This technology can become a strategic stimulation for organisations to achieve competitive advantage and sustainable growth. Previous BDA research, however, has focused more on introducing more traits, known as Vs for big data traits, while ignoring the quality of data when examining the application of BDA. Therefore, this study aims to explore the effect of big data traits and data quality dimensions on BDA application. This study has formulated 10 hypotheses that comprised of the relationships of big data traits, accuracy, believability, completeness, timeliness, ease of operation, and BDA application constructs. This study conducted a survey using a questionnaire as a data collection instrument. Then, the partial least squares structural equation modelling technique was used to analyse the hypothesised relationships between the constructs. The findings revealed that big data traits can significantly affect all constructs for data quality dimensions and that the ease of operation construct has a significant effect on BDA application. This study contributes to the literature by bringing new insights to the field of BDA and may serve as a guideline for future researchers and practitioners when studying BDA application.

A Dimensionality Reduction Algorithm for Unstructured Campus Big Data Fusion

Data modeling and dimensionality reduction are important research points in the field of big data. At present, there is no effective model to realize the consistent representation and fusion of different types of data of students in unstructured campus big data. In addition, in the process of big data processing, the amount of data is too large and the intermediate results are too complex, which seriously affects the efficiency of big data dimension reduction. To solve the above problems, this paper proposes an incremental high order singular value decomposition dimensionality (icHOSVD) reduction algorithm for unstructured campus big data. In this algorithm, the characteristics of audio, video, image and text data in unstructured campus student data are tensioned to form a sub-tensor model, and the semi-tensor product is used to fuse the sub-tensor model into a unified model as the individual student tensor model. On the basis of individual model fusion, the campus big data fusion model was segmented, and each segmented small tensor model was dimensioned by icHOSVD reduction to obtain an approximate tensor as the symmetric tensor that could replace the original tensor, so as to solve the problem of large volume of tensor fusion model and repeated calculation of intermediate results in data processing. The experimental results show that the proposed algorithm can effectively reduce the computational complexity and improve the performance compared with traditional data dimension reduction algorithms. The research results can be applied to campus big data analysis and decision-making.

COMPARISON OF MACHINE LEARNING CLASSIFICATION ALGORITHMS FOR PURCHASING FORECAST

With the development of computer technologies and invention of internet, many concepts have entered our lives. With the starting of wide usage of globalized internet network, concept of machine learning has emerged in time for smarter management of data flow in big dimensions. In line with technological developments, all activities began to be carried to digital environment and as a result of this, concept of e-commerce has entered our lives. E-commerce is one of the areas where machine learning is used most widely. By examining product purchasing situations in accordance with data available at the enterprises, various researches have been made for selection of most appropriate model in order to predict future data. In the study it was mentioned about concepts of e-commerce and machine learning and by applying Logistic Regression, Naïve Bayes and Support Vector Machines being machine learning classification algorithms, it has been aimed to determine the model having best accuracy ratio. JEL codes: L81, C11, C38, C39, C53

The effect of chemical structure of carboxylate molecules on hydroxyapatite nanoparticles. A structural and morphological study

Being the most abundant non-macromolecular organic component of bone, the role of citrate (Cit) in hydroxyapatite (HA) crystallization is of high relevance. In this work we have investigated the influence of hydroxycitrate (CitOH) and glutarate (Glr) on HA crystallization in terms of particle growth, composition, and morphology in comparison to Cit. CitOH and Glr have been selected for this work because they share the same backbone structure of Cit but bear different functional groups in the central region. Our data has revealed that CitOH strongly inhibits HA crystallization more efficiently than Cit. CitOH-HA nanoparticles are composed of platy, elongated particles similar to those of Cit-HA but they are ca. twice smaller and have a lower crystal order. On the other hand, Glr does not inhibit HA crystallization as Cit, but leads to the formation of OCP platelets that convert with maturation time to HA nanorods with larger aspect ratio than Cit-HA. In comparison to Cit-HA samples, Glr-HA nanoparticles have bigger dimensions, and higher structural order. Overall, our data reveal that the central carboxyl group of Cit is involved in the selective binding with HA crystal surface and in regulating HA crystal growth. The results of this work highlight new possibilities to control the formation of HA for designing advanced bioactive materials and give new insights on the role of the structure of Cit in regulating the HA morphology.

Learning global solidarity in the Covid-19 pandemic?

In a letter published on March 30, 2021, 24 world leaders have called for global solidarity in the fight against the Covid-19 pandemic. This commitment to act in solidarity with low-income countries however was won under duress, and it was in part at least self-serving. Can this still be called solidarity? On the basis of a functional view on solidarity the paper argues that states can indeed act in solidarity, if they accept costs to assist others with whom they recognize similarity in a relevant respect. States can act in solidarity, or they can fail to act in solidarity, also in situations of duress and if solidary acts also serve their own interests. The paper concludes that if this is true for the Covid-19 pandemic it is also true for the climate crisis, where damage of even much bigger dimensions are to be prevented. Also in regard to anthropogenic global heating, nobody is safe until everyone is safe.

Optimization Analysis of Tennis Players’ Physical Fitness Index Based on Data Mining and Mobile Computing

Tennis is a very explosive, continuous, and intense sport, including many continuous short‐term explosive actions. It has the characteristics of short‐term, high‐intensity, high‐density training, and it belongs to the category of purely competitive skills. In the competition, athletes must maintain good physical condition, physical fitness, and long‐term endurance in order to demonstrate outstanding technical and tactical skills. Therefore, this paper proposes a mobile processor performance data mining framework MobilePerfMiner, which uses hardware counters and iteratively uses the XGBoost algorithm to build a performance model, ranks the importance of the microarchitecture events of the big data task, and reduces the performance big data dimension, so as to optimize the big data algorithm according to the performance characteristics described. Undoubtedly, the comprehensive monitoring of the sports training process is complex system engineering. The main monitoring includes three aspects: physical condition, technical and tactical skills, and intelligence. Sports technology is reflected in the ultimate load. According to the convenience and actual needs of the research, this article will discuss the methods of evaluating tennis training load and the actual technical and tactical parameter characteristics that can be obtained by studying the characteristics of tennis, namely, kinematics. Parameters for noncontact testing, the next step is to discuss the appropriateness and necessity of the load, as well as the technical and routine monitoring of tennis training ability. The final experimental results show that it can improve the physical energy of tennis players by more than 17%.

ELABORATION AND RESEARCHES OF HICHLY EFFECTIVE INSTALLATION FOR VIBRO-BLOWING DEHYDRATION OF DISPERSIVE WASTE OF FOOD PRODUCTIONS

There are schemes of equipment for dehydration of damp dispersive waste of food productions (spirit grain, beer pallets, beet pulp, coffee and barley slag) analyzed in this article. These wastes at the majority of food enterprises of Ukraine are poured out onto the ground and that leads to environment pollution. However, in case of dehydration of these wastes to humidity 20 – 25%, they can be used as valuable additions to agricultural forages or as high-energy fuels. Thus, the problems of waste utilization and protection of nature from pollutions are resolved simultaneously. Besides, the enterprise gets a profit from the sales of forage additions or fuel. The known equipment for mechanical dehydration, for example, the screw-presses and the decanter centrifuges, provides the waste final humidity no less 74 – 76%, therefore waste demand of an additional drying after the dehydration at this equipment. That brings to a significant increase of energy expenses. An application of the vibro-blowing dehydration at the installations with the hydraulic pulse drive provides waste final humidity 20 – 25%, but these installations are complex by design, have big dimensions and high cost. A drying in pulverizing or in vacuum dryers is most power-consuming dehydration method (expenses of energy - 740 ÷ 2248 kW h/ ton of dehydrated waste). Equipment for the chemical and biological dehydration is the large multiple-unit complexes with low specific productivity. Therefore, article authors offer a scheme of the installation with the combined unbalanced and hydraulic drive that has a relatively simple design, compact dimensions, high reliability and at the same time, in correspondence with the authors’ estimation, will provide necessary, above indicated humidity. Also equations for determination of the main working parameter – the pressure in the press-form of the proposed installation are presented in the article.

Распределение сигналов синхронизации и данных цифровой антенной решетки на базе волоконно-оптических линий

The article deals with the practical aspects of synchronization and data transferring in multichannel phased array systems, especially in systems with big antenna dimensions. In multichannel passed array antenna commonly used an optical analog signals distribution scheme for RF and heterodyne signals and wired interfaces for control and digital data. For modern digital antennas the data transferring and synchronization method, based on digital fiber optic channels, was presented. The schemes, constructions, and algorithms of the method are described. The method was realized as SDR system using FPGA with soft-processor core. For data transferring the 8b/10b code is used. The following result of experiment are discussed: digital optical lines are resistant to signals distortions, can transfer big data massive with minimal delay, have excellent synchronization capabilities at quite low cost.

Cognitive and personality test as a predictor of religious education achievement among students of religious program of Islamic schools in Indonesia

Students' admission aims at selecting students who can adapt to the school environment and predict students' academic success. The best student admission system is needed to determine the success of religious education in schools that have a religion-based. This paper presents the results of correlation between predictive test study, cognitive and personality tests toward the students’ Islamic achievement in Islamic Subject. This research used a quantitative approach and a survey using three measuring instruments; a learning achievement test, cognitive test, and Big Five Personality test. The subjects of this study were 1396 students from 10 Islamic Senior High Schools conducting religious major program in Indonesia. The results of this study indicate that cognitive tests and personality types are significant predictors of religious education achievement. Specifically, verbal tests and reasoning have been significant predictors of religious education achievement as well. Furthermore, from five dimensions of Big Five Personality, the strongest type of personality, openness to experience and conscientiousness are vigorous predictors of the religious education achievement. Agreeableness, extraversion, and emotional stability, however, do not have a significant influence on religious education achievement. Further research can reach the entire national admission system of state Islamic senior high schools in Indonesia namely Islamic senior high schools Insan Cendekia, which is also a state boarding school in Indonesia.

Experimental study of convective heat transfer during liquid piston compressions applied to near isothermal underwater compressed-air energy storage

Abstract Compressed air energy storage may be an important asset for large-scale implementation of renewable energies. The REMORA technology combines quasi-isothermal compression with maritime construction efforts. Convective heat transfer in liquid piston compressors have not been thoroughly studied so far, but its understanding is deeply important to characterize the system's behavior. An experimental analysis of air compression using liquid piston is proposed for chambers with big dimensions, which leads to the development of several correlations. From these assessments, it is possible to describe the presence of two different convective heat exchange patterns, as well as the liquid piston position in the transition between them. A numerical model is developed by employing these correlations. The comparison between numerical and experimental results enables the validation of such correlations for a specific set of parameters.

Estimates of the Solution of the Balance Model Considering the Environmental Factor and Investment

The article explains the nonlinear balance model that considers disposal and recycling of wastes and investments. The suggested model is the equilibrium prices model in which the costs of harmful wastage disposal and recycling are considered. Besides, there are nonlinear interrelations between the branches of production, which allows us to predict the release of useful products, which is necessary for the economistsanalysts who are engaged in forecasting the manufactured products. For the model which is described by a system of differential equations, the conditions are created when the system of differential equations has only one solution. The paper defines the conditions under which this model is solvable and has a nonnegative solution, if at the same time the given values can be negative. For the model the methods of creating bilateral estimated solutions are adapted; the method of improving bilateral estimation is offered. Unlike the methods of searching the precise solution, the application of the method of bilateral estimation facilitates successful solution of tasks with big dimension of the processed models, without resorting to direct integration. The results of this article can be used in the solution of specific tasks of mathematics, economics, biology and other tasks with nonlinear interrelations.

CONSTRUCTION HISTORY AND DIGITAL HERITAGE. EXPERIMENTATIONS ON RENAISSANCE DOMES IN CAMPANIA (ITALY)

Abstract. The paper describes an ongoing research project granted by the University of Naples Federico II (2017–2020) concerning masonry domes considered as visual poles in the historic urban landscape and as a constructively vulnerable built heritage. Studies focus on Renaissance domes in Campania region (Naples included) and combine established strategies with innovative ones for the knowledge of visible/invisible parts. Verticals and curved structures are investigated with a unitary approach, together with the pre-reinforcements placed during the construction phases or for later strengthening. These topics deal with issues crucial for the domes’ study: firstly, the overlapping of inner and outer surfaces that hide structural elements and do not enable their comprehension. In addition, we must consider the recurring difficult inspection or inaccessibility due to the big dimensions and heights from the ground. All these factors, together with the fact that decorated surfaces are a limit for the traditional diagnosis, require new investigation strategies – remote and by non-destructive methods – so as to document the invisible both for emerging and for underground parts. A model for knowledge characterized by the interlacement of ‘humanistic’ interpretation and bottom-up/bottom-down surveys is discussed. The understanding of what is invisible to direct inspection is considered a stimulating frontier for proposing innovative dissemination tools for the comprehension of cultural heritage, able to reach new communicative horizons related to the construction of complex forms of architecture. The transposition of the research outcomes into digital “accessible” data aims at having impacts for sharing a broader cultural awareness of the built heritage historical constructive significance.

Research on equipment fault prediction expert system based on big data dimension reduction

Due to the complex structure and massive volume of large equipment in petrochemical enterprises, it was very difficult to carry out inspection and maintenance work. The traditional expert system used a single knowledge base and reasoning machine, so the processing efficiency and prediction accuracy were low. In this paper, the dimensionality reduction which is used to process a large amount of physical information collected by the sensors, remove redundant components and extract main characteristic parameters. Meanwhile, combined with the powerful pattern recognition and judgment ability of fuzzy neural network, the forward reasoning mechanism and error back propagation keeping continuous training correction until meeting the accuracy requirements, the expert system gave the equipment fault prediction conclusion. Finally, taking main fan oil station circulating oil pump and motor of heavy oil catalytic cracking unit and nine stages of bearing damage as monitoring objects, the fault predictions was implemented by the following steps: data collection, feature extraction, dimension reduction of big data and expert system with the fusion of fuzzy neural network, and it is proved that the expert system with fuzzy neural network based on dimension reduction can greatly improve the convergence speed.

Solar Concentrator PDR with solar tracking

The reduction in conventional fuels consumption can be accomplished through the use of solar energy, transforming it into thermal energy throught a solar collector. There are a lot of solar collector kind, but the solar concentration way, specifically the parabolic dish reflector technology, or just PDR solar concentrator, offers one of the most efficient paths to achieve high quality thermal energy. Usually, the PDR solar concentrator are designed in big dimensions in order to generate electrical energy; nevertheless this technology could be used in minor scale in order to generate solar concentration high levels to achieve enough thermal energy to satisfy hot water demand in residential buildings, homes and even the industry. The prototype here presented was developed in four phases: The parabolic dish, the gear box and mechanical support device, the sun tracking control system and finally the system integration and operational tests. The four phases conjunction results in a totally operative prototype with the capability of achieve temperatures of 400 ºC, over a concentration focal point under partially cloudy day conditions.

Big Data Quality Dimensions: A Systematic Literature Review

Although big data has become an integral part of businesses and society, there is still concern about the quality aspects of big data. Past research has focused on identifying various dimensions of big data. However, the research is scattered and there is a need to synthesize the ever involving phenomenon of big data. This research aims at providing a systematic literature review of the quality dimension of big data. Based on a review of 17 articles from academic research, we have presented a set of key quality dimensions of big data.

Hubungan Dimensi KepribadianThe Big Five Personality Dengan Tingkat Kesejahteraan Psikologis Narapidana

The Big Five Personality is one of the theories of personality that consists of five personality dimensions, namely: Agreeableness, Openness to New Experience, Extraversion, Neuroticism and Conscienstiousness. Thirty-five prisoners of cases of narcotics and drug trafficking into subjects in this study. In testing the assumptions of normality of data, showed that the data were normally distributed. This is indicated by the value of significance (p-value) greater than 0.05. As for the correlation test, showed that Openness to Experience significantly positively correlated with Psychological Wellbeing (r = 0.504; p = 0.002). Extraversion significantly positively correlated with Psychological Wellbeing (r = 0.420; p = 0.012). Agreeableness positively correlated significantly with Psychological Wellbeing (r = 0.620; p = 0.000). Constinousness significantly positively correlated with Psychological Wellbeing (r = 0.473; p = 0.004). Neuroticism is negatively correlated significantly with Psychological Wellbeing (r = - 0.479; p = 0.004).
 The purpose of quantitative research with correlational approach is to know the relationship between the Big Five personality dimensions with Psychological Wellbeing on inmates in Prisons Women Class II A Malang. Further research is expected to contribute to the Women's Prison Class II A Malang in order to carry out the task of coaching the inmates. Conclusions from the analysis of the data is that the four dimensions of personality Big Five Personality significantly positively associated with psychological well-being. Except for Neuroticism personality dimensions are significantly negatively associated with psychological well-being.