Reviewerly/exHarmony huggingface dataset:
Methods and Technologies of Internal Speech Recognition by Non-Invasive Neurointerfaces

neurosurgeon Wilder Penfield.He described the results of his work in the monograph "Language and Brain Mechanisms, " still relevant for neurologists and cognitive specialists [5].This can also include studies using deep brain stimulation [6] and transcranial magnetic stimulation, which began to be carried out relatively recently.Functional neuroimaging methods are currently leading methods in the study of the neurophysiology of internal speech.Let us judge which structures are functioning at the moment:-Functional magnetic resonance imaging (fMRI) and positron emission imaging of certain brain regions;-diffuse-tensor MRI allows visualization of conducting brain pathways connecting these areas; magnetoencephalography (MEG) makes it possible to measure and graphically represent magnetic fields that are formed due to electrical activity of the brain.The structure responsible for understanding speech is the Wernicke zone, the posterior part of the upper temporal gyrus.This area is adjacent
IR Spectroscopic Characters Of Garnets and Spinels - a Potential Discriminative Tool for Diamond Exploration

Garnet and chromite are two important indicator minerals for diamond exploration.Most reported studies were focused on their compositional characters (1,2,3,4, 5,6,7,8] over the years.Although the structural refinement analysis |9, 10, 11], and spectroscopic studies (12, 13, 14] of garnet and spinel have been done in detail, but there is no one using the structural characters of garnet and chromite to discriminate primary diamond sources so far.In recent years, the structure and spectroscopic features of above two minerals have been studied by the authors (15,16,17 for garnet and 18,19 for chromite].It has been discovered that there are some pecu¬ liar garnets and chromites to diamondiferous kimberlitic rocks.An IR microanalysis method has been established [18].In order to contrast the spectroscopic character with its chemical composition of these two minerals because the IR spectroscopic and compositional information could be obtained from the same grain.
The Analysis of the Feasibility of Optimizing Elman Neural Network

Elman Neural Network (ENN) is a widely used typical feedback-type neural network model. Considered to represent an optimization of Back Propagation Neural Network (BPNN), while ENN does perform better than BPNN in some certain properties, is also inherits some defects of BPNN. For example, both BPNN and ENN are highly nonlinear neural network models with poor generation capability. Such deficiency determine that these two models perform worse when dealing with some prediction problems involving linear influencing factors. To address this, the rest of this paper presents an optimized model based on ENN (ENN-DIOC) by introducing direct input-to-output structure into ENN, and analyzes the feasibility of this optimization. Combined with the experiments completed by predecessors, it can be proved that it’s feasible for ENN-DIOC to improve the prediction accuracy and add linear factors to basic ENN.
Non-Functional Requirements Elicitation

Non-Functional requirements elicitation is one of the most important activity in requirements engineering. Non-functional requirements define the quality attributes of software system. If this analysis is not done properly, it may cause for problems in further phases that in turn may lead to failure of the software. Hence the non-functional requirements analysis has to be given at most priority in software development. This paper presents survey on different approaches proposed for Non-Functional requirements analysis
Synthesizing 64 Bit Architectures and E-Business using SULA

Read-write models and cache coherence have garnered great interest from both biologists and system administrators in the last several years. Given the current status of wearable algorithms, steganographers ur- gently desire the exploration of fiber-optic cables, which embodies the essential principles of e-voting technology. We argue that despite the fact that congestion control and evolutionary programming [29] can connect to realize this intent, e-business and linked lists can interact to fix this quandary.
A Unified Analysis of Bank Customer using Machine Learning

In order to discover information, virtual data evaluation involves trendy computer tools and display. The use of various digital research methodologies has become quite frequent throughout society. The aim of this proposed model is to provide a new vision of customer relationship administration through visual representation and interactive techniques. Special mentions of the investigation include that consumers have a better change on consumer truthfulness in the banking sector, specifically with the expenses towards a better direction, the bond between them becomes much firmer. Lastly, comments are presented on how to make the consumer satisfied and increase their trust. They are consistently hunting for new techniques to improve their business profits like, correct commodity marketing to best consumers, accurate use of own channels, visitation on a low level to bank branches for everyday money withdrawals and etc. A unified analysis of bank customer's helps to identify the person’s judgment and decides whom to distribute the services of bank and how much credits can be offered up to a limit. It also helps the bank issuer’s understand profile of their consumers. The model uses different algorithms (KNN, Logistic Regression XGB Classifier, Decision tree and MLP classifier) to train and test the data and then analyses the best algorithm to perform the task. As customer profiling in a bank is a highly requested service for such task, a unified analysis of the same consumer segmentation is specially customized for money minting industry.
Cypher fundamentals

The conceptual, technical and sociopolitical origins of CCTech are discussed with a view to providing insights as to important drivers of this technology that remain relevant today. The contributions of key persons and ideas that preceded Satoshi Nakamoto’s Bitcoin are discussed including Whitfield Diffie & Martin Hellman, Wei Dai, David Chaum, Paul Zimmerman, Cynthia Dwork & Moni Naor, Nick Szabo, as is the underlying ideas of the cypherpunk movement as set out by Timothy May and Eric Hughes. The connection between money, privacy and the concept of identity are introduced. The consequences of the shift from the initial coin offering to the securities token offering, a result of the application of securities laws, is considered. The chapter concludes with an introduction to the concept of the New Prospect, ranging from new institutional and business concepts to Mark Miller and Eric Drexler’s application of economist Friedrich Hayek’s ideas to computer science.
Recognition of Offline Gujarati Handwritten Disjoint Consonants using Pattern Matching

Image processing is one of the most popular field nowadays. Recognition of the offline isolated handwritten characters is an area which got lot of attention within the field of Image Processing. Various techniques have been proposed in the area of online and offline handwritten character recognition (HCR). In future HCR is the key factor for the transformation of written or printed text into system understandable format. Thus, providing a boost to digitization era. Gujarati is one such language which has many challenges in creation of an accurate OCR. Researchers have achieved good accuracy in the field of online Gujarati handwritten character recognition. This paper introduces a pattern recognition system which is able to recognize isolated offline Gujarati handwritten characters with higher accuracy. Experiments have been done on sub set of ( g, `, l, x, h ) consonants using a total data set of 6750 handwritten consonants by different individuals. The experimental results achieved a markable contribution in the field of handwritten character recognition.
Virtual tours as a way to enhance the cognitive activity of educational migrants

The article studies the possibilities and features of the application of innovative methods of boosting the cognitive activity of foreign applicants for higher education in teaching. As a basic form, it is proposed to use a virtual tour as a way of learning Ukrainian as a foreign language. The introduction of information technologies in the educational process has changed educational goals. In the future, we can expect a transition from online learning to a blended model. There is a reorientation to a person-centered approach. The main task of training is not only a transfer of knowledge but a formation of skills of obtaining and processing information, the formation of high-level thinking skills: analysis, synthesis, evaluation. The use of multimedia capabilities of the computer has qualitatively changed the perception of information by foreign graduates. Today, the computer at the classes of Ukrainian as a foreign language is a visual aid, a means to increase emotionality, an encyclopedia, an electronic textbook, an accessible tool for knowledge control, as well as a possibility to effectively present new material, show a prepared presentation and more. The aim of the article is to study the activation and effectiveness of cognitive activity of educational migrants and consider the basic principles and stages of preparation and conduct of educational tours using innovative technologies within the formation of linguistic and cultural competence of foreign students to make them master Ukrainian as a foreign language better. The most effective means of competence development is the use of project methods in the educational process. The virtual tour implements the principles of modern pedagogical activity: the principle of competence approach – obtaining a high result through the activities of higher education, the principle of cognitive activity – through independent, creative activity to obtain new knowledge.
Signature Extraction and Recognition from Bank Cheque ImageSignature Extraction and Recognition from Bank Cheque Image

Automatic signature extraction and recognition from document images is an open research problem. Signature verification is of two types; static and dynamic, and has two approaches; writer dependent and writer independent. Signature verification system in case of bank cheque image should essentially be an error prone system to elude the fraudulent transactions. In this work, a three layer signature verification system is proposed, which is writer independent and offline signature verification system. Graphometrical and FAST features are extracted from the signature images and are given as inputs to the classification algorithms. The proposed signature verification model is a combination of three classification algorithms; artificial neural network, Gaussian mixture model and image matching models, to circumvent the fraudulent transactions. The overall performance accuracy of proposed process is 99%.
Detection of Signature Based Forgeries Using Artificial Neural Network

Signature plays an important role in banking, financial, commercial etc. Signature may be unique for each person. In olden days, no techniques were used to find the forged signature and it becomes a tremendous strain for human brain. Sometimes the forged signature may also believe as an original one. But nowadays, there are so many methods to detect the forged signature. This paper explains about identifying the forged signature from original signature. The signatures are preprocessed then the features such area, centroid coordinate, eccentricity, kurtosis are extracted. Then it is classified using Artificial Neural Network effectively. The result is analyzed by changing the hidden nodes present in the Neural Network. The performance is evaluated using the parameters such as TPR, TNR, FPR and FNR.
OCR rules P.E. changes aren't discriminatory

Case name: Letter to: Sacramento City College , No. 09‐18‐2168 (OCR 04/25/18).
Application of Blind Deconvolution Algorithm for Deblurring of Saturated Images

Image Restoration is a field of Image Processing which manages recuperating a unique and sharp image from a debased image utilizing a numerical corruption and reclamation model. This investigation centers around rebuilding of corrupted images which have been obscured by known or obscure debasement work. Image rebuilding which reestablishes an unmistakable image from a solitary haze image is a troublesome issue of assessing two questions: a point spread function (PSF) and its optimal image. Image deblurring can improve visual quality and mitigates movement obscure for dynamic visual examination. We propose a strategy to deblur immersed images for dynamic visual examination by applying obscure piece estimation and deconvolution demonstrating. The haze portion is assessed in a change space, though the deconvolution model is decoupled into deblurring and denoising stages by means of variable part
Protected Entree Design for Big Data Knowledge in Cloud

Because of the trouble and limit, cryptography to a cloud is to be a standout amongst the best properties for huge information stockpiling and access. Anyway confirming the entrance authenticity of a client and safely refreshing cryptography in the cloud dependent on another entrance approach chosen by the information proprietor are likewise basic difficulties to make cloud-based enormous information stockpiling down to earth and dynamic. In this paper, we propose a safe and access control dependent on NTRU cryptosystem for huge information. Our procedure enables the cloud server to productively refresh the cryptography when another entrance arrangement is distinguished by the information proprietor, who is additionally ready to confirm the update to counter against duping practices of the cloud. It conjointly allows the information proprietor and qualified clients to successfully confirm the authenticity of a client for getting to the information, and a client to approve the data given by various clients to legitimate plaintext recuperation.
Core Banking System Scalability Review

In carrying out the digital transformation, bank has to find their optimal routes to exploit the Open Banking opportunity and minimize or manage any threat. However open Banking models will be making implication on the increasingly hit from the external parties. It will be new and more unpredictable data volumes as third parties request access to the banking system. Bank has to prepare their Banking system on the Enterprise Architecture, and one of the concerns is on the scalability. For the traditional core banking system, the platform of mainframe and other legacy technology could remain the bottleneck to agility and scalability. In this paper, scalability testing and analysis are carried out to verify whether the traditional banking core system running on the power platform can be scalable to support open banking strategy. The results found were that the core banking system could be scalable, but needed a lot of enhancement on the core banking application side, as well as capacity upgrading on the server side.
International PM Perspective

After having worked with individuals and projects from each continent, well not Antarctica yet, it would seem practical to share some further experiences and perspectives that have helped learn personal growth lessons. At the end of every project the lessons learned is a key document, which will help reduce struggles for each project manager in the company on future projects. Many of these examples are related to relationships more than just the core scope, schedule and budget, but this is frequently where project managers need the most work.
Mobile Technologies and Their Role in the Development of Musical Ear

The processes of informatization transform the environment of professional activity of the contemporary musician, form new educational needs of students of various musical specialties, cause changes in the activity of the teacher-musician.This is due, in particular, to the use of digital educational resources, the widespread introduction of techniques and methods of network interaction and modern music and computer technologies (MCT), which have a wide range of capabilities.These possibilities are truly limitless, they allow you to find new artistic worlds.One of the actual problems of musicology is the study of the processes associated with the spread of information culture and their influence on the formation of the contemporary musician, in particular the formation of musical ear.The authors of the article analyze the possibilities of mobile technologies in the field of development of musical hearing of children's musical schools and children's schools of arts.Based on the results of many years of practice of teaching solfeggio with the use of mobile technologies and the conducted pedagogical experiment, the authors conclude about the high educational potential of cloud-oriented technologies in the system of contemporary musical education.Mobile technologies can significantly expand the forms and methods of teaching solfeggio.The authors of the article note the need for further scientific and pedagogical research in this area related to teaching with the use of modern mobile technologies, the development of training programs and professional retraining of teachers of musical and theoretical disciplines.
Utilization of digital materials as a research resource for historical materials and applied interdisciplinary research for history and archaeology, including the research work and projects of Prof. Sato and Prof. Kikuchi

The preservation of historical artefacts is an important means of understanding more about the past. Japan is home to thousands of stone inscriptions, many of which are not stored in research institutions of museums, but rather, are scattered across the country in places like roadsides or graveyards in rural locations. While these inscriptions might well be of interest to local residents, there is a need to increase awareness of their cultural importance. A team led by Hiroki Kikuchi, who is based at The Historiographical Institute within The University of Tokyo in Japan, is working to create a database which will digitise 2,700 inscription rubbings. The database will be open to the public and will provide a fascinating historical narrative as well as an important research resource.
The Role of Data Preprocessing System on Web Log Files for Mining Students Access Logs

Nowadays, WWW has grown into significant and vast data storage. Every one of clients' exercises will be put away in log record. The log file shows the eagerness on the website. With an abundant use of web, the log file size is developing hurriedly. Web mining is a utilization of information digging innovations for immense information storehouses. It is the procedure of uncover data from web information. Before applying web mining procedures, the information in the web log must be pre-processed, consolidated and changed. It is essential for the web excavators to use smart apparatuses so as to discover, concentrate, channel and assess the ideal data. The information preprocessing stage is the most significant stage during the time spent web mining and is basic and complex in fruitful extraction of helpful information. The web logs are circulated in nature also they are non-versatile and unfeasible. Subsequently we require a broad learning calculation so as to get the ideal data.
Keyphrase Generation with a Seq2seq Model

Keyphrases provide the core information of the source text, thus useful in many applications.Previous researches focus on extracting the keywords from the original document but miss those absent keyphrases unseen from the source.So we propose a generative model based on seq2seq RNN, which can generate both present and absent keyphrases by capturing the semantic information of the source.We adopt the large vocabulary trick to construct the target words corpus so as to improve the efficiency.We also introduce the feature-rich encoders to leverage the linguistic and statistical information in the source.Additionally, we incorporate the switching generator-pointer mechanism to extract those out-of-vocabulary words from the original document.To evaluate our model, we conduct two tasks, i.e., predicting present keyphrases and generating absent keyphrases, on real-life datasets.The results prove the effectiveness of our model as it outperforms the state-of-the-are models consistently and significantly.
Location based popularity analysis of Twitter data

This research aims to analyze location based twitter data to measure the popularity of the products/persons or any given user parameter. For this purpose this work has integrated sentimental analysis, location based system and ontology. An application with a novel user interface has been developed to search and visualize the data on Google map. This research work uses publicly available and location enabled twitter data. This work also has the capability to process tweet data without user’s locations. The main contribution of this research is the integration of sentimental analysis on location based Twitter data. Another significant contribution is the development of a novel user interface, which allows the user to search on a map interactively with multi-focusing features on Google map. This integrated sentiment analysis work efficiently performs location based popularity scaling on products, persons, brands or any given topic.
Performance Evaluation of Block based Video Watermarking after Attacks

In today’s era use of digital media is most popular way of communication. Digital media covers images, videos and animations available online. The easy methods of accessing, copying and editing digital media have made them more popular. With several advantages these easy methods of copying and editing data have created some big issues like ownership identification. This increases the demand of protecting online digital media. Watermarking is solution of such problem. In this work, a block-based method has been proposed for video watermarking that uses a key at the time of embedding and extraction. Some frames are selected from the video according to a key. Watermark is embedded on the selected frames after dividing into parts called blocks. Each part of the watermark is embedded in one selected frame of the video. This method increases the security of the system as the complete watermark cannot be extracted without knowing the positions of watermarked frames and the position of the block in that frame. Watermarking is performed in the Discrete Wavelet Transform domain after scaling of watermark data. To show the authenticity of proposed scheme various attacks are applied on different watermarked video frames and extracted watermark results are shown under different tables.
Human Action Recognition using Scaled Convolutional Neural Network

Deep learning is current buzz word in domain of computer vision. In this work, a method for human action recognition based on a variation of General Convolutional Neural Network (GCNN), called Scaled CNN (SCNN) is proposed. In GCNN, weights of the network are updated in every epoch of training to minimize the classification error. In SCNN, the weighs are first computed using gradient descent algorithm as in GCNN, and then multiplied by scaling factor. Scaling factor is calculated using statistical measures, mean and standard deviation of the frames. Since statistical measures vary from video to video, scaling factor adapts to these changes. As the statistical information from the frames is directly used to alter the weights, it results in minimizing the error faster as compared to GCNN. Results of the proposed method prove that higher accuracy can be achieved with less number of epochs if scaling is used.