bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Digital Documents and Materials in Civil and Arbitration Procedures
Authors: M. Golovanov Nikolay , . . 
Published: July 2024

The research topicality is due to the broad use of digital documents and materials in civil circulation, and the imperfection of the existing legislation in determining their legal status. This situation negatively influences the evidential significance of the digital documents and materials when presented in civil and arbitration procedures.The article objective is to reveal the lacunas in the legal regulation of digital documents and materials as evidences when investigating disputes in general and arbitration courts, and to elaborate proposals for their elimination.The key approach to the research was the legal analysis of legislative and departmental normative legal acts mentioning digital documents, and the analysis of special literature in this sphere of social relations.The main results of the research are: formulating the definition of a digital document setting its most general features and enabling to establish this definition as a legal one; setting the criteria for distinguishing a digital document and a digital material, an original and a copy of a digital document; defining digital documents and materials as direct or indirect evidences, depending on their evidential significance.The conclusions presented in the article can be used by legislators when correcting the norms of the Civil Procedural Code of the Russian Federation (CPC RF) and Arbitration Procedural Code of the Russian Federation (APC RF), other special laws, and by judicial agencies when administering justice on civil cases.Â Â
Plants Nutrition and Growth Stimulation with the Help of Nanotechnologies
Authors: I. Churilov G. , G. Churilov D. , G. Churilov S. , N. Borychev S. , V. Byshov N. , V. Churilova V. , D. Polischuk S. 
Published: July 2024

The consistent use of some branches of agrochemical science in crop growing is in the concept of a comprehensive system approach we propose to the issue of plants nutrition and growth stimulation with the help of nanobiopreparations based on copper and cobalt nanopowders. We propose to optimize the technology of a number of agrochemical measures, and more precisely, to reduce them to a single pretreatment of seeds with a preparation containing necessary trace elements in the nano form.This article presents toxic and stimulating effects of using nanoparticles in agro and biotechnology. The developed bio preparations, based on nanoparticles of metal-trace elements (iron, cobalt, copper), have a number of advantages over existing analogues and they are as it follows:â€¢ multifunctional action;â€¢ low consumption rates of preparations up to 1.0 g per hectare seeding rate, while pre-sowing treatment can be combined with dressing, which does not require additional energy costs;â€¢ a comparative assessment of the toxicity of nanopreparations compared with salts of trace elements (iron and copper sulphates, cobalt chloride) proves that salts are 8-10 times more toxic than nanopreparations;â€¢ low cost of nanopreparations (NP) compared with the cost of an equivalent dose of traditional mineral micro fertilizers and drugs to prevent plant diseases;â€¢ ecological safety.The uniqueness of the proposed technology lies in the fact that its use in agriculture does not require any special equipment or an increase in the staff of the enterprise. In the process of applying the proposed preparations, the natural processes of agrobiocenosis are not disturbed and soil fertility is preserved.The effect of nanobiopreparations on living organisms and the effect of â€œlow dosesâ€ compared to substances in the usual physical-chemical state, make possible to obtain scientifically based and objective results of the effect of nanoparticles on plants nutrition and growth stimulation.Â Â
Design of an On-Chip Tracking ADC
Authors: Mohan Manju , Seenu N , R Nair Shyam , Vignesh U P 
Published: July 2024

Data acquisition and conversion systems require analog signals to be converted into a digital form that can be used for further analysis. The analog signals are mostly output of sensors and transducers which transform the real-world signals into electrical signals. These electrical signals are modified to digital form by using Analog to Digital Converters (ADC). This conversion involves sampling followed by a quantizationÂ of the input signal thus will be converted to digital signal. The bandwidth of the ADC is restricted by the sampling rate and the quantization error should be kept as low as possible for better accuracy. This paper emphasis on the On-Chip design of a 12-bit Tracking ADC using PSoC which is highly reliable for digitizing the slowly varying signals. Complication encumbered in the logic that connects comparator and counter is replaced by using dual comparators, and an XOR gate. The proposed design has immense leverage in providing stable and constant data for instantaneous signal value. The major involvement is shown in making the design very simple, by efficiently using the available components, thus providing much accurate and stable digital data for further processing the slowly varying signal.Â Â
Knowledge-Based Requirements Engineering in Detecting Ambiguity
Authors: Sudah Sinpang Jacline , Sulaiman Shahida , Idris Norsham 
Published: July 2024

Requirements engineering is a phase where the elicitation and analysis of requirements are crucial. Low quality requirements could cost a software project to experience failure, as it does not meet usersâ€™ needs. One of the causes of poor quality requirements is ambiguity. Software engineers or more specifically system analysts normally gather requirements in natural language where it is easy for both developer and stakeholders to understand each other. However, natural language in requirements gathering is prone to ambiguity. Ambiguous requirements will cause developers to understand differently from what the stakeholders actually require. Thus, it is important to avoid ambiguous requirements. As there are many types of ambiguity, this study focuses on the vagueness of functional requirements. The study implements rule-based reasoning in knowledge-based requirements engineering to detect vagueness. Rules for the proposed prototype tool are obtained from journals and experts in requirements engineering. The evaluation shows that diverse categories of vagueness can be detected earlier using the proposed technique and its tool.Â Â
The Role of Denisonâ€™s Organisational Culture on Email Usage among Academician in Malaysian Private Universities
Authors: SHAH BALI MAHOMED ANUAR , G. MCGRATH MICHAEL , ZHI YUH BONG , OTHMAN ZULBASRI , SALWA SHEIKH MOKHTARe SITI 
Published: July 2024

academician in Malaysian private universities. For the research, a scale of measurement was used based upon the concepts that are found in values as well as practices in regards to organisational culture developed by Denison and Mishra (1995) model namely Involvement- Capability Development (ICD), Consistency-Agreement (CA), Adaptability-Organisational Learning (AOL) and Mission- Goals & Objectives (MGO). In this study, Technology Acceptance Model (TAM) developed by Davis (1989) was used as part of the perspective theory on technology adoption, using the constructs; perceived ease of use (PEOU) and perceived usefulness (PU) as mediator for organisational culture and email usage. Data used in the study were based on questionnaires of 128 academician from two Malaysian private universities. The study found that all constructs of organisational culture were having significant in the relationship to the perceived ease of use (PEOU) and perceived usefulness (PU) with ICD, AOL and MGO having significant positive relationship with PEOU and PU while CA has significant negative relationship with PEOU and PU on email usage. Finally, PU and PEOU had significant positive relationship with email usage while PEOU had significant positive relationship with PU on email usage. This means that the usage of email among academician in Malaysian private universities depend on both the userâ€™s perception of email usefulness and the perception of ease of use.Â Â Â
The Effects of Physical Property Estimation on Packed Column Distillation Simulation with a Rate-based Mode
Authors: Sei Lee Young , Mori Hideki , Lee Kiyoung , Man Lee Joon 
Published: July 2024

Background/Objectives: we investigate the effects of estimation models for physical properties on the rate-based simulation and discuss what we should be aware of for obtaining better simulation results.Methods/Statistical analysis: Three kinds of physical property models considered are an activity coefficient, a thermodynamic factor, and a liquid excess molar volume. We use experimental data obtained from a pilot-scale plant for comparison with numerical examples. We investigate the effects of estimation models for physical properties on the rate-based simulation and discuss what we should be aware of for obtaining better simulation results.Findings: The thermodynamic factor models do not affect largely the simulation results in the distillation simulation where the mass transfer resistance of the vapor phase film is dominant.The liquid excess molar volume of the ternary mixture of Methanol, Ethanol, and Water shows at most 3% deviations from the averaged molar volume. It affects the simulation results markedly where the composition of the liquid mixture passes through the region of the large excess molar volume.Improvements/Applications: The simulation results indicate that even small difference in continuous operation becomes much pronounced in batch operation with multicomponent systems.Â Â
Toward Accurate Music Classification Using Local Set-based Multi-label Prototype Selection
Authors: Seo Wangduk , Seo Sanghyun , Lee Jaesung 
Published: July 2024

Background/Objectives: Multiple music tags enable quick searching and selection of music clips for by end-users to listen to. Our goal is to improve the accuracy of automatic music categorization.Methods/Statistical analysis: We propose a local set-based multi-label prototype selection to remove noisy samples in datasets without transforming multi-label datasets to single-label datasets by searching the local set of each sample. To validate the superiority of the proposed method, we use ten multi-label music datasets and Hamming loss as a performance measurement, which counts the symmetric difference between predicted labels and ground truth labels.Findings: Considering time and cost, manual categorization of a large collection of music clips is generally impractical. As such, an automated approach for addressing this task through the training of music tags annotated from an online system is employed. In the real world, multiple labels can be annotated to a music clip by users of an online system, resulting in unintended noisy samples due to inaccurate annotations. Conventional methods attempt to transform multi-label datasets to single-label datasets that can yield additional computational cost and unintended removal of non-noisy samples. In this paper, we propose a novel prototype selection method for multi-label music categorization. Experimental results indicate that the proposed method performed the best performance on nine music datasets. From the experiment of CAL500 dataset, multi-label classification performance based on the training samples selected by our proposed method was 0.1402, which indicates that 15,020 labels on average were correctly classified for 100 test samples. Compared to the second-best performance by the compared method, our method was able to classify 245 more labels.Improvements/Applications: Experiments using ten different musical datasets showed that the proposed method demonstrated better performance than the compared methods.Â Â
Loss Analysis in Accordance Switching State of 3kW Full-bridge Converter with Current Doubler Rectifier
Authors: Park Je-Suk , Park Young-Un , Shin Duck-Shick , Kim Dae-Kyong 
Published: July 2024

Background/Objectives: The losses mostly dissipate to the thermal and reduce the output efficiency of the power conversion system.Methods/Statistical analysis: loss analysis of the 3kW DC-DC converter in accordance switching state through thermal module of circuit analysis tool.Findings: Loss analysis of a DC-DC converter was performed using the thermal module function of circuit analysis tool. Loss of power semiconductor is analyzed by modeling power semiconductor device for loss analysis with device database editor.Improvements/Applications: The thermal of power semiconductors analyzes the thermal by adding a thermal equivalent resistor to the device for power semiconductor loss analysis. The results are expected to be helpful for heat dissipation design. Future research will add inductor loss analysis.Â Â
Indirect Photon-Counting Detector with a GAGG Scintillator for Low-Energy Photon Detection
Authors: Baek Cheol-Ha , Lee Hakjae , Kim Daehong 
Published: July 2024

Background/Objectives: The aim of this study was to explore the properties of indirect detection using a scintillator and silicon photomultiplier, as scintillators are highly sensitive for breast cancer detection.Methods/Statistical analysis: Silicon photomultipliers (SiPM) and Cerium-doped Gd3Al2Ga3O12 (GAGG) scintillator crystals were used to fabricate a scintillation detector, and its characteristic of spectroscopy were compared to the results of LYSO and CsI using Î³-ray spectroscopic measurement. The resulting energy resolutions of each scintillation detector, comprising a single crystal scintillator (volume size: 3Ã—3Ã—2 mm3) and a SiPM (active area: 3Ã—3 mm2) for a Î³-ray source, such as 241Am, were measured and compared.Findings: The 137Cs source yields an energy resolution of 5.23 and 20.31% at 661 keV for the GAGG and LYSO scintillators, respectively. Alternatively, because the CsI scintillator did not yield a distinct energy peak, an energy resolution was not measured. The 241Am source yields an energy resolution of 28.88 and 36.12% at 59.5 keV for the GAGG and LYSO scintillators, respectively. Measured energy peaks of the 241Am source were 62.7 and 64.6 keV for GAGG and LYSO scintillators, respectively. The energy peak of the 241Am source for CsI was not measured because the CsI scintillator did not yield a distinct energy peak of 137Cs source for calibration.Improvements/Applications: The GAGG scintillator could improve the energy resolution of low-energy source than LYSO and CsI scintillators.Â Â
The Combined Effects of Lee Silverman Voice Treatment and Abdominal Respiration on the Maximum Phonation Time in Parkinson's Disease
Authors: Byeon Haewon 
Published: July 2024

Background/Objectives: The purpose of the our study was to evaluate the effects of a respiratory rehabilitation the forced vital capacity, voice intensity, and maximum phonation time (MPT) of patients with hypokinetic dysarthria.Methods/Statistical analysis: This study was carried out on 32 patients with Parkinson's disease (PD). All subjects were randomly assigned to a treatment group (n = 17), which received both abdominal breathing training and LSVT, and a control group (n = 15), which only received abdominal breathing training. The forced expiratory volume at one second (FEV1) was measured in the sitting positing. The coordination of respiration and vocalization was measured by using MPT.Findings: The results of ANCOVA, which controlled the pre-test with a covariate, showed that the control group (CG) and the treatment group (TG) were significantly (p<0.05) different in FEV1, MPT, and vocal intensity. The results of parameter estimation revealed that the TG had significantly longer MPT (1.9 seconds longer on average) than the CG and the vocal intensity of the TG was significantly stronger (3.1dB higher on average). On the other hand, FEV1 significantly increased in the TG and the CG after 4 weeks of treatments compared to the baseline. However, there was no significant difference between TG and CG.Improvements/Applications: The respiratory rehabilitation composed of LSVT and abdominal breathing was effective in improving not only the vocal intensity of patients with PD but also the coordination of respiration and vocalization.Â Â
Fake Currency Detection Using Image Processing
Authors: Saxena Ankur , Kumar Singh Pawan , Prasad Pal Ganesh , Kumar Tewari Ravi 
Published: July 2024

Since last few years, as a result of the great technological advances in color printing, duplicating and scanning, counterfeiting problems have become more and more serious. In the past, only the printing house has the ability to make counterfeit note, but today it is possible for any person to print counterfeit bank notes simply by using a computer and a laser printer at house. Therefore the issue of efficiently verifying counterfeit banknotes from real ones via automatic machines has become more and more important. Counterfeit notes are a problem of almost every country but India has been hit really hard and has become a very acute problem. There is a need to design a system that will helpful for recognition of paper currency notes with fast speed and in less time. This proposed system describes an approach for verification of Indian banknotes. The currency will be checked out by using image processing techniques. The approach consists of a number of elements including processing of image, detection of edge, image segmentation, drawing out characteristic, comparing both images. The image processing approach is discussed with MATLAB to verify the parameters of note. Image processing involves changing the nature of an image in order to improve its visual information for human interpretation. The image processing software is a collection of functions that extends the capability of the MATLAB numeric computing environment. The result will be whether note is real or fake.Â Â
A Mixed Approach for Approximation of Higher Order Linear Time Invariant Systems
Authors: Singh Ramveer , Chatterjee Kalyan , Singh Jay 
Published: July 2024

This work suggests a technique for order reduction of larger order mathematical model into lower order by combining Modified Inverse Distance Measure (MIDM) and time moment matching criterion. The constant coefficients of the denominator of reduced model are attained by proposed algorithm named MIDM and numerator coefficients of the same are obtained by using the suitable number of time moments and Markov parameters in the set of equations of Improved Pade Approximations (IPA). The suggested method of order reduction is equally useful for both Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) dynamic systems. The simplicity of the proposed method has been validated through various linear mathematical models taken from literature. To get into the touch of a researcher, the qualitative measure and dynamic analysis of the proposed reduced model output has been elaborated via error index and time/frequency response comparisons respectively.Â Â Â
Issues of Accountability in Cloud Computing Environment
Authors: Kanta Mohanty Surjya , Mishra Samaresh , Kumar Pattnaik Prasant 
Published: July 2024

In an accountable Cloud Computing Environment the system able to handle Â even the smallest action being performed by any entity in the environment and trace the entity that performed such as action to hold same accountable for mishap/risk if any. It is very essential that evidence of all the activity stored and processed may be maintained and stored for recovery in the future if required. This stored/maintained data are required to have enough information so that a particular activity can be properly scrutinized. This process should be an iterative process in order to achieve excellence in the system of the Cloud. This paper addresses the issues of accountability in a cloud computing environment.Â
Object Recognition with Improved Features Extracted from Deep Convolution Networks
Authors: Manohar K , Irfan S , Sravani K 
Published: July 2024

Object identification is a method for identify an exact object in an image. Object identification algorithm depends on matching, learning, and pattern recognition using appearance based feature technique. Object recognition has various method to detect objects itâ€™s include feature extraction and machine learning methods, deep learning search as CNN. The deep learning convolution neural network (CNN) has been proved to be very efficient in feature extraction. CNN is compressed of one or more convolution layers and then follow by one or more totally connected layers. In Image types, the work with classifiers aims at explore the most appropriate types for high level deep features. The feature extracted from the image plays a significant role in image type. It is the process of retrieving the main data from the raw data, its finding the set of parameters that recognize the object uniquely. In feature extraction every nature is represent by a feature vector itâ€™s become identity. In this work the features extracted from CNN applied as input to train machine learning classifiers and perform image classification. A systematic comparison between various classifiers is made for object recognition.Â Â
Security and Privacy Mechanisms of Big Data
Authors: Amarendra Reddy P. , Gouse Sheikh , Bhaskara Reddy P. 
Published: July 2024

Big Data advances in three key areas like storage, processing and analysis. Hadoop architecture is produced to store extensive measure of data through adaptable parallel handling with speed to get the outcomes. Organizations must guarantee that every single big data bases are resistant to security dangers and vulnerabilities. Amid data gathering, all the important security assurances, for example, continuous administration should to be satisfied. Remembering the big size of big data, Organizations should to recollect the way that overseeing such data could be troublesome and requires uncommon endeavors. Be that as it may, making every one of these strides would help keep up buyer protection. The Security and Privacy challenges for Big Data might be sorted out on big data community. Securing the framework of big data frameworks includes Securing appropriated calculations and data stores. Securing the data it is of vital significance, so we need to guarantee that data scattering is security saving and that touchy data is ensured using cryptography and granular access control. Overseeing tremendous volumes of data requires adaptable and conveyed answers for Securing data stores as well as empowering effective reviews and examinations of data provenance. At long last, the streaming data that is rolling in from various endpoints must be checked for respectability and can be utilized to perform continuous examination for security episodes to guarantee the strength of the framework. The explanation behind such ruptures may likewise be that security applications that are intended to store certain measures of data can't the huge volumes of data that the previously mentioned datasets have. Likewise, these security advances are wasteful to oversee dynamic data and can control static data as it were. In this way, only a customary security check can't distinguish security patches for nonstop streaming data. For this reason, we require full-time protection while data streaming and Big Data Analysis.Â Â