Reviewerly/exHarmony huggingface dataset:
Evaluation of modern GPGPU technologies for image processing

Image processing has high computational requirements. As many papers (including [Frisk 2010; N. Zhang and Wang 2010; Yang et al. 2008]) have indicated, a number of image processing operations can be optimized by heavy parallelization of the computation. Currently, one of the best options for parallelized image processing is using general purpose computation on graphics processing units (GPGPU).
Japanese Character Recognition with Microstrip Line Networks

Character recognition, a topical field seen from the large number of practical applications, allows the generation of characters in electronic media from printed documents or images. The Japanese language is one of the most difficult language because of the very large number of characters or classes of objects to be identified, and many recognition systems have been proposed. A new way of recognizing Japanese printed characters is presented in this paper. The proposed method is based on the modeling with microstrip lines of the character topological structure and the analysis using microwave engineering methods. The spectral distribution of the resonance frequencies is used as a local descriptor in the recognition process. A deep convolutional recurrent network is used for the classification step. The proposed method ensures good accuracy in the Japanese character recognition process using the lowest number of descriptors among the methods described in the literature. The character recognition method has been tested by analyzing the first ten resonant frequencies of the five Japanese vowels, and 99.9% character recognition has been provided for 20% dispersion of the microstrip line segment lengths.
Digital Media Distribution Platform Using Amazon Web Services

Digital Media Distribution platforms are necessary for delivering multimedia content. Classic client-server approaches and 3-tier architectures are not optimized for media processing. In this paper, we present a serverless modern digital media platform for media content distribution based on the Amazon Web Services (AWS) cloud platform. The proposed platform uses CloudFront for static content cashing, S3 for data storage, Lambda for the dynamic content and Elastic Transcoder for media format conversion. This platform offers reduced loading times and efficient media format conversion/distribution.
The scientific conferences of universities of culture on library and information activities: The information support in digital environment

The authors analyze how the university scientific conferences in library and information studies are being reflected on the Internet. The findings of the study conducted by authors draw the attention of professional community to the problem of representation of academic proceedings of the Russia’s institutes of culture. These conferences are seen as a professional communication channel and a means to improve professional competences in the whole library and information industry. The authors analyze the problems of accessing the proceedings of scientific conferences held by the universities of culture, which are the essential component of the Russian library science advance. Through monitoring the www-sites of the universities of culture and studying the Internet resources in the area, the authors review the existing ways of distributing information and propose the options for presenting full-text science information to provide efficient information exchange in the library and information sphere. The resources being built with the open data technology, providing a multiaspect search and storage of information for repeated and free use, are proposed as a priority. The findings of the study evidence that for the moment, the complete representation of the research activities at the universities of culture is unavailable, and there is a need to apply the resources proposed by the authors.
Policies and mechanisms for enhancing the resource management in cloud computing: a performance perspective

Resource management is among the critical challenges in cloud computing since it can affect its performance, cost, and functionality. In this paper, a survey on policies and mechanisms for enhancing the resource management in cloud computing is proposed. From a performance perspective, several resource management schemes for cloud computing are investigated and qualitatively compared in terms of various different parameters such as performance, response time, scalability, pricing factor, throughput, and accuracy, providing some fundamental knowledge based for researchers in the cloud computing area. We also classified various cloud computing techniques based on various policies like capacity allocation, admission control, load balancing and energy optimisation. Further, we divided defined techniques on the basis of various parameters like low, medium, high time span time techniques, reliability, performance, availability to name a few.
PELATIHAN PENGGUNAAN MS OFFICE PADA STAF KANTOR DESA MASSAMATURU KABUPATEN TAKALAR

The activity of community service was located in Massamaturu village office of Takalar Regency. This activity aims to give the training of using Microsoft Excel and Microsoft Word to office staffs of Massamaturu Village in Takalar Regency with total of 15 people. Some staff have not fully understood on how to use some features on both Microsoft Excel and Microsoft Word. Creating table, tabulation, indent, picture insert, autocorrect, the use of shortcut, the use of formula function in Microsoft Excel still need more training. The result of training is hoped to increase skills of using Microsoft Excel and Word. Microsoft Excel is used to manage spreadsheet data, particularly processing of budgeting and financial statement. Meanwhile, Microsoft word is used to create some documents, such as letter of statement, business license, and cover letter. The result of this training is the increase of knowledge and skills on the use of Microsoft Excel and Microsoft Word to office staffs of Massamaturu Village by using assessment indicators, such as training tasks on workbook.
Meme Ucu Çatlağı ile İlgili YouTube’daki Videoların İncelenmesi

Objective: The object of this research is to evaluate the quality of information on Youtube videos related to nipple cracks.Material and Method: Youtube was searched and a research related to nipple cracks was performed in December 2018. Videos watched by 2 faculty members who had a PhD degree were evaluated and grouped (Excellent, average, poor) for their sources, contents and recommendations. For data analysis, Shapiro Wilk, Kruskal Wallis H test, Pearson Exact Chi-Square test were used. Results: In the research, the first 50 videos on YouTube were analyzed. 30 (60%) of these 50 videos were included in the study, whereas 20 (40%) were excluded from the study for various reasons. A statistically significant difference (p=0.001) was determined when the relationship between the video source and the grouping as the content was compared, and the source of all the videos grouped as excellent was determined as the health personnel. A statistically significant difference (p=0.006) was found when the relationship between the video sources and the recommendations provided in the videos was compared, and it was determined that the combined treatment was recommended only by the health personnel. Conclusion: Although the videos in which the source is the health personnel are useful for the viewers, there are also videos containing misleading information. Therefore, they are not a reliable source of information for the viewers. Thus, it is recommended for the healthcare personnel to guide people to choose videos related to nipple cracks uploaded by the health personnel.
Design of Video Mosaic System

With the development of embedded technology and the popularity of ultra-high-definition display, people’s requirements for the quality of display are increasing. This paper designs a four-way high-definition video mosaic system. The system uses four-way high-definition 1080P image as input. After image data buffering, frame synchronization, multi-channel mosaic, and other processing, it can output 3840 × 2160@60 Hz ultra-high-definition video image in real time through DP1.2 interface. The system adopts FPGA chip, which type is XC7K325TFFG900-2. With four DDR3 memory chips, it can process multi-channel image data at least 24 Gb/s in real time. After the program is mapped to the chip, the resource consumption of look-up table is 25.96%, the resource consumption of BRAM is 40.45%, and the total dynamic power consumption is less than 5 W. The experimental results show that the system supports continuous video acquisition and real-time playback, and has broad application prospects in video surveillance, medical consultation, multimedia display, and other fields. At the same time, the hardware system is expected to be popularized in the acquisition, transmission, and processing of three-dimensional stereo images.
Motion Planning of a Robotic Arm using an Adaptive Linear Interpolation Crossover and Variable-Length Move Sequence Genome

The ability to perform robotic arm motion planning is a necessity in the design of autonomous and intelligent robotic systems. Motion planning allows the autonomous robotic arm to maneuver its end-effector in an unstructured environment whilst avoiding obstacles on the workspace. This ability is particularly important in processes with pick-and-place operations and varying object positions. In this study, a genetic algorithm-based motion planning for a 4-DOF robotic arm was developed. The developed genetic algorithm operates on a variable-length genome that consists of changes in joint angles. These changes in joint angles represent the end-effector's move sequence. The results show that adaptive linear interpolation crossover (ALIX) improves the convergence of the motion path towards minimization of end-effector error and path length. On average, the end-effector error is 1.4 mm with a maximum path length deviation from a straight line of about 50.4 mm tested on extreme target points. Testing with obstacles present in the workspace shows the ability of the algorithm to generate solution paths to avoid them as well.
Increasing CNN Representational Power Using Absolute Cosine Value Regularization

The Convolutional Neural Network (CNN) is a mathematical model designed to distill input information into a more useful representation. This distillation process removes information over time through a series of dimensionality reductions, which ultimately, grant the model the ability to resist noise and generalize effectively. However, CNNs often contain elements that are ineffective at contributing towards useful representations. This paper aims at providing a remedy for this problem by introducing Absolute Cosine Value Regularization (ACVR). This is a regularization technique hypothesized to increase the representational power of CNNs by using a Gradient Descent Orthogonalization algorithm to force the vectors that constitute their filters at any given convolutional layer to occupy unique positions in ℝ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> . This method should in theory, lead to a more effective balance between information loss and representational power, ultimately, increasing network performance. The following paper examines the mathematics and intuition behind this Regularizer, as well as its effects on the filters of a low-dimensional CNN.
Algorithmic Design and Implementation for Performance Optimization of Workflows Based on Trac

To improve grout interaction in ticket management system, ameliorate dynamics of business processes and optimize the rate of resource sharing. An optimization algorithm for performance optimization of workflow is proposed, and the system is implemented by Ticket-Workflow. The mathematical model and Java business process management workflow engine as the technical framework, which is used to solve the problem of business process changes, improve collaboration efficiency of research activities and enhance scalability and flexibility of the system. The heuristic algorithm is designed and is compared with other algorithms through experiment. The performance superiority of the proposed solution to previous solutions is proved through experiments.
The Mobile Media Communication And The Doctor-Patient Relationship In The Case Of Children Ent Disorders

Communication through mobile media software represents one of the new trends that influence almost all fields of human activities. The applicability of such instruments are limitless when we speak about social groups type influence upon postmodern consumer behavior. Authors aim to investigate throughout a qualitative marketing research issues regarding the communication between doctors and parents having children with ENT (Ear, Nose, Throat) specific disorders, the relationship that is developed and the degree in which the mobile media communication software represents an instrument which may help into the process of relationship and/or can influence opinions and perceptions already formed about a ENT doctor. The findings can originally contribute to a better understanding of this new kind of phenomena - mobile media mediated communication between doctors and patients as the research is one of the first within the field. Respondents show a high propensity to use the specific software analyzed, although because of the high level of emotional personal involvement the decision to choose a certain ENT doctor is not influenced so much by the pressure or opinions of the reference group.
Economic Optimization of Shell and Tube Heat Exchanger using Adaptive Mutation Strategy Jaya Algorithm

Shell and Tube Heat Exchanger (STHE) is the important device in the many industries like power plant. The cost of the STHE is more and this in-turn requires economic optimization of the STHE design. This research aims to provide the economic optimization of the STHE with Adaptive Mutation Strategy (AMS) with Jaya algorithm. The Jaya algorithm has the considerable performance in the STHE design optimization. The AMS technique is applied in the Jaya algorithm to escape from the local optimum based on the operator. The proposed AMS-Jaya algorithm in design optimization is compared with other existing methods to investigate the performance. The capital cost of the design provided by the AMS-Jaya algorithm is $ 3891.02 and the capital cost of the Jaya algorithm design is $ 3986.92. The numerical analysis shows that the developed AMS-Jaya algorithm has more performance in economic optimization than existing methods.
On Decoding Problems, Lattices and Generalized Concatenated Codes

Information transfer and storage play an important part in the technical society we live in. A big challenge is the unreliable nature of wireless communication along with failure of storage devices and other technical equipment. Another challenge is the vast amount of data that needs to be handled. Claude Shannon created the mathematical theory of communication in the late 1940s. Today, this subfield of information theory is known as coding theory. One of the main problems that coding theory deals with is the question of how to achieve fast, efficient and reliable communication over an unreliable channel. Reliability can be achieved by adding redundancy to the transmitted information. This, however, comes at the price of lower efficiency since we have increased the amount of data that is transmitted over the channel. Hence, the different goals are conflicting, and one particular solution is usually only suitable for certain applications. The process of adding redundancy to the message is called encoding. The set of all encoded messages is called a code, while one encoded message is called a codeword. When a codeword is sent over an unreliable channel the channel might distort the transmitted codeword, and hence the receiver is left with the task of recovering the transmitted codeword from the distorted one. This is referred to as decoding. Lattices are mathematical objects that, at first glance, appear to be simple. However, they are the source of many hard problems, and they are useful in many different applications, including coding theory and cryptography. Formally, a lattice is a finitely generated subgroup of a real vector space. Generalized concatenation is a method of building new codes from existing ones. Codes obtained this way are known as generalized concatenated codes. The strength of generalized concatenation is that one can create long codes with good properties from short codes. Moreover, generalized concatenated codes can be decoded using decoders for the component codes. However, the decoding algorithm for generalized concatenated codes is still complex, and any developments in this area will make the adoption of these codes in practical applications easier. This is very important since many good codes can be obtained by generalized concatenation. This thesis deals with decoding problems, or more specifically, the design of efficient decoding algorithms for specific codes. We consider decoding algorithms for lattices and generalized concatenated codes.; Informationsoverforing och -lagring ar en viktig del av dagens teknikbaserade samhalle. Utmaningarna ar dock manga. Tradlos kommunikation ar till sin natur opalitlig och lagringsenheter och annan teknisk apparatur gar ofta sonder. Utover detta ar det fragan om enorma datamangder som bor processeras och lagras. Claude Shannon lade grunden for den moderna informations- och kodningsteorin under 1940talet . En av de stora fragestallningarna inom kodningsteori ar hur man kan uppna palitlig kommunikation over en opalitlig kanal. Detta kallas…
Braille Based Steganography System Using Dynamic Key Exchange

Cryptography provides a method for obscuring the original data, whereas steganography provides a means for obscuring the mere presence of data. Many different carriers are used such as audio, video, images etc. to hide the data. Images are the most commonly used carriers. Once the data is hidden, the image can then be sent to the receiver. This method is secure because only the sender and receiver are aware of the communication. Many different steganographic techniques have been proposed for secure data communication, but these are highly vulnerable to attacks when the presence of hidden data is exposed. In this paper, an improved image steganography method is proposed. The data is initially encrypted using RSA algorithm. Instead of using the traditional Least Significant Bit encoding, the proposed system uses a method similar to the Braille form of character representation. Using this representation, the encrypted text and the key are encoded into the image. The resultant image is the steganographic image that is used for communication. This proposed method has proven to be more secure than the existing methods. The results and experiments have been explained in detail.
Define success for yourself, given Arrow’s Impossibility Theorem

Abstract “Define success for yourself, given Arrow’s Impossibility Theorem” explains different voting methods, including plurality voting, run-off voting, sequential run-off, Borda count, and dictatorship, and explains how Kenneth Arrow’s Impossibility Theorem proves that, in an election with three or more candidates, the only fair voting system is a dictatorship. That is, every voting method other than a dictatorship has a known problem with fairness. Mathematics students and enthusiasts are encouraged to consider the many “candidates” for defining “success” in mathematical and life pursuits before letting their vote be the only vote in electing a personal definition of success. This way, Arrow’s Impossibility Theorem assures a fair outcome. At the chapter’s end, readers may check their understanding by working on a problem. A solution is provided.
No-Reference Video Quality Metrics Using Wavelet Transform with Several Noises

This paper presents a blind assessment of video quality called the no-reference video quality metric. The proposed scheme used video watermarking that involves 8x8 blocks of Haar and Daubechies (D4) wavelet transform within the RGB domain. However, several noise types have experimented, those are salt-and-pepper, Gaussian blur, Gaussian and distort ripple. In addition, JPEG compression has been tested within the proposed method. In this paper, a robust scheme is proposed against the attacks of swapping, frame dropping, statistical analysis and averaging. The experimental results of the proposed system give acceptable outcomes. The Daubechies4 filter has given a better result than Haar filter. The perceived video quality metric has been performed through Peak Signal to Noise Ratio (PSNR) and Root Mean Square (MSE) metric. Daubechies4 has given the best result as compared to Haar filter and Discrete Cosine Transform (DCT).
Correlating the Machine Learning Models for Automatic Error Detection and Correction in Medical Images

Medical image has always been considered as a significant research area when it comes to advanced analysis in the critical disease diagnosis process. There has been massive archival of research works based on the medical image concerning the classification and analysis. In this regard, this paper has identified two core techniques that have been frequently used over images viz. i) optical character recognition and ii) machine learning. Both the system has its own benefits and limitation as witnessed in many research works. The contribution of this paper is to find out an essential correlation between these two frequently used models over images so that a novel form of solution can be developed in future applications based on medical images. This paper briefs all the essential information available on the existing approaches of both the system focusing mainly on both the error correction methods and learning methods. It is anticipated that the finding of this paper will assist in deploying a better decision to choose machine learning and it's applicability shortly.
The technology of picking up the first break of surface microseismic based on constraint

Abstract In this paper, a constraint based first break acquisition technique for surface monitoring is proposed. This method enables users to automatically pick up the starting point and the ending point of the first arrival position after simply observing the starting point and the ending point of the first arrival position and determining the position. Secondly, because the first break automatic picking method mentioned in this paper will analyze the data characteristics of each channel carefully to find the first break time point in each channel accurately, so that the accuracy of first break picking is significantly improved.
Control of Electronic Devices Using Neural Network Based Sundanese Speech Recognition

This paper describes how speech recognition automatically uses the local language that originated from Indonesia, namely the Sundanese, which can control electronic devices in the home. Sundanese is the second most widely used regional language in Indonesia after Java. Voice recognition using Sundanese is carried out in this study to be able to control several electronic devices directly with high accuracy. The method used in the introduction of Sundanese is the Mel Frequency Cepstral Coefficient (MFCC) extraction method and identification of backpropagation-based neural networks. There are 10 Sundanese instructions used in the introduction to speech as input to the system, and each instruction has 2 to 3 Sundanese syllables. The output used by the author in this paper is five household electronic devices, to turn on or turn off controlled output using 2 Sundanese instructions. The data used in the backpropagation training process is 300 data; each instruction is 30 data. The results of training weights can produce an accuracy rate of 96.7% when testing the system. The control system uses the MFCC method and artificial neural network backpropagation algorithm so that the program works and Sundanese language voice recognition is good.