Reviewerly/exHarmony huggingface dataset:
Sparse Weighted Multi-view Possibilistic C-Means Clustering with L1 Regularization

Sparse clustering algorithms create clusters with a sparsity of features and are effectively applied to extremely high-dimensional single-view datasets containing irrelevant features, noise data, outliers, and missing data. Multi-view datasets contain features extracted from various measuring devices using the same sample. Each distinct group of features constitutes a specific view of the data. Although these data are extracted from diverse settings and domains, they must be highly correlated since they are from the same sample. Most of the sparse clustering methods can only handle single view datasets. Thus, they may encounter difficulty obtaining the desired result when clustering multi-view datasets, leading to poor performance. Therefore, there is a need to develop a suitable multi-view clustering method to address the above problem. In this paper, we propose an algorithm called Sparse Weighted Multi-view Possibilistic C-means with L1 Regularization (S-WMV-PCM-L1) designed to perform multi-view clustering as well as view and feature selection with Possibilistic C-Means (PCM) as its base function and using L1 (LASSO) Regularization as a penalty term. This algorithm uses a weighting scheme within its clustering framework to determine the comparative significance of each view of data points and features. Experimental results using real-world datasets show the feasibility and effectiveness of our proposed algorithm. Also, S-WMV-PCM-L1 performs better when compared to other existing multi-view clustering algorithms.
Neoplastic and non-neoplastic breast lesions in a rural teaching hospital at Tamil Nadu: A retrospective study

Introduction: Breast malignancy is one of the leading cause of cancer death in women, which is a complex disease, comprising of distinctive histological patterns and it is the responsibility of the pathologist to differentiate a benign lesion from a malignant one.This study was done to evaluate the age, gender, laterality, frequency and histopathological features of non-malignant and malignant lesions in a rural hospital.Materials and Methods: This retrospective study was done in the Department of Pathology Rajah Muthiah Medical College and Hospital for a period of 5years from January 2017 to December 2021.The data was collected in a proforma with relevant detailed informations.The excised specimens were received in buffered formalin, processed, sectioned and stained with routine Haematoxylin and Eosin stains.Results: Out of 570 cases in breast lesions, the female cases reported were 92.1% and males 7.9%.The maximum number of breast lesion were seen on the left side followed by right side and bilaterality with 47.9%, 44.4% and 7.7% respectively.The non-malignant lesions accounts for 79.3% and the malignant lesions 20.7%.Among the non-malignant lesions Fibroadenoma with 60.2% and in malignant lesions Infiltrating ductal carcinoma with 93.2% were maximum encountered. Conclusion:In our study, most of the malignant lesions were in the late stage, due to lack of awareness, which can be rectified by conducting camps and awareness programmes.Further this study emphasizes the importance of early diagnosis and management in malignancies to reduce the morbidity and mortality.
“Open Archives” academic guide to develop the concept of knowledge management in the digital environment

Today’s competences of librarians in terms of their digital training are reviewed. “The Open Archives” education and methodological guide offered by RNPL&amp;ST’s research team is introduced. The product lies within the concept of open archives and open access. It is suggested that students on their master’s or doctor’s programs start the Open Archives course already mastering knowledge, skills and competences in digital activities. The authors specify key professional and special competences targeted at library and information goals in the modern digital environment, which is useful for librarians interested in open access, and open archives issues. The R&amp;D team at Moscow State Linguistic University has been adapting the Open Archives model. The article is prepared within the State Order No. 075-00642-21-00 “Design and development of the system of Open Archive of Integrated Information Resources of Russian National Public Library for Science and Technology as the modern system of knowledge in digital environment: On the way to open science” for the years 2020–2022.
An Efficient Certificate-Based Encryption Scheme Without Random Oracles

Certificate-based encryption combines traditional public key encryption and identity-based encryption while preserving their features. Compared with other public key cryptosystems, the advantage of certificate-based encryption are: (1) solving the problems of certificate revocation in traditional PKI and third-party queries about certificate status, (2) providing more efficient PKI that requires fewer infrastructures, (3) overcoming the key escrow problem inherent in the identity-based encryption. In this paper, we propose an efficient certificate-based encryption scheme which meets the chosen-ciphertext security under the complexity assumption of the truncated decision q-augmented bilinear Diffie-Hellman exponent problem and the decision 1-bilinear Diffie-Hellman inversion problem in the standard model. The proposed scheme requires computing only one bilinear pairing in the standard model, our scheme enjoys better performance, especially on the computation cost.
DIGITAL HUMANITIES IN SCIENTIFIC DIMENSIONS

The article is devoted to the outlining the features and prospects of scientific perception of the problems of digital humanities. The concept of digital humanities in diachronic and synchronous scientific reception is considered, the main functional advantages of digital humanities in the context of rethinking existing scientific achievements and in the context of forming new transdisciplinary scientific paradigms are determined. It is defiined that the digital humanities significantly expands the operational capabilities of research through the use of digital tools that create the preconditions for the formation of various automated classifications; to trace hierarchical connections, multilevel correlations, interactions between phenomena that are the objects of humanitarian research, etc. It was found that, depending on the specific goals and objectives, digital humanities projects can be implemented using a variety of digital tools, including the creation of space-time, visual projections, data processing in quantitative and qualitative parameters. The implementation of digital projects involves various forms of their presentation as individual sites, applications, online search resources, various databases, user-created content, data visualization, immersive objects and spaces, interactive documents. It is determined that the concept of transdisciplinarity forms the theoretical basis for the productive use of information and educational resources aimed at forming a single information and educational environment. Transdisciplinary ontologies of knowledge systems are considered as important means of creating network-centric cognitive services that provide analysis, structuring, selection of information according to certain criteria, which allows its further interpretation and application taking into account diverse structural relationships.
An Approach to the Segmentation of Dense Crowd Scenes

Crowd segmentation is an important pre-stage in the analysis of crowd behaviour. The segmentation method proposed in this paper is intended for segmentation of dense crowds of people. The method consists of four main stages: feature extraction, tracklet generation, creating of Voronoi cells of dense optical flow (VcOFs 1 ), and hierarchical clustering of VcOFs. Each of these four steps is described in detail. The method was tested on a dataset consisting of eighty video clips from ten video sequences,
A Vocational Career Advisory Application Built Using Unsupervised Machine Learning Frameworks

As freshers experience their examinations and follow their intrigued courses, it is significant for them to evaluate their qualities and perceive their inclinations so as to make sense of in which vocation field their inclinations and abilities would get them. It will assist them with improving their yield and motivate their wants to be engaged at their planned profession and settle in that. Likewise, for recruiters when employing candidates in the wake of surveying them in every single different way, these profession suggestion frameworks assists them with deciding the job title the candidate ought to be held in depending on his/her outcomes and different evaluations. This paper centers essentially around the prediction of the software engineering space of applicants in the vocation field. Most appropriate space as per interests and capabilities of the applicant is anticipated and reasonable employment opportunities pertinent to the area are shown. The fresher can go after his favored position from the arrangement of employments shown.
A Simple and Fast Technique for Takri Touching Text Segmentation Using Local and Non-Local Features

The paper defines a new model for Takri touching text segmentation (T3S), which uses simpler statistical operations to locate exact segmentation point and generates faster results. An analysis of existing Indian scripts touching text segmentation techniques is also provided in the paper. The analysis inferred higher accuracies with recognition based approaches which are computationally and time extensive and, work better with huge datasets. Also, most of these have been developed for headline Indian scripts only. The proposed T3S model provides significant segmentation accuracy using segmentation-based approach thus, generating faster results. Also, it works well with small datasets, which is feasible with the diverse ancient low-resource scripts of India like Takri. The model has been implemented on Takri text, a class of non-headline Indian regional scripts. Thus, it provides a benchmark algorithm for conducting further research in the field. A dataset of 1465 touching consonant pairs in printed Takri script is prepared using connected component segmentation for segmenting Takri text from the manually collected archival data in printed Takri script. The proposed T3S technique is implemented on the dataset prepared and the results are critically analyzed with the existing Indian scripts touching text segmentation approaches, on the basis of accuracy achieved.
Efficient Computation of Hepatitis Blood Smear Image Encryption Using Enhanced Chaotic Technique for Cloud Storage

The method of injecting information into a host to fulfil a particular function is referred to as information hiding also known as steganography. It is necessary to secure medical information of sensitive diseases like HIV, TB, HBSAG, etc. In this work are explored the biomedical image hiding tactics in the photo domain of H.264/AVC where we secure patients medical information stored in institutions cloud with cryptography and steganography techniques. First, the basic structure of data hiding is understandable by coupling the condition of an item with a context (i.e., sequences of bits). Here, we proposed a novel enhanced methodology of chaotic technique image encryption for encrypting tested HBSAG positive blood samples and supporting documents. Then the encrypted image (cipher image) is embedded to a cover image with a security key using LSB bit substitution method. Finally, these high sensitive medical data are stored to cloud with high level of security. This method performs with good level of MSE and PSNR.
The Probability Background

The mathematicalMeasure framework for statistical decision theoryDecision theory is provided by the theory of probability, which in turn has its foundations in the theory of measure and integration.
Searching the Proper Term Weights a Lexicon Specialized in Ipos

The objective of this study is to introduce new term-weighting schemes and to investigate whether these schemes outperform the existing ones in IPO tasks. Specifically, various textual sentiments with novel term weighting schemes aim to effectively gauge the tone of S-1 filings to explain IPO underpricing. The empirical analysis is conducted on a sample of 2,502 U.S. IPOs over the period 1997 to 2016. The proposed term weighting schemes are specialized in IPO tasks and seem to outperform the existing ones in the literature in terms of statistical significance. In conclusion, the choice of the proper term weighting is indicated as very important and reliably influences the quality of each approach to quantify document tone.
A Study of Heterogeneous Database Integration Based on Web Service and XML

At present, the vast majority of databases used by the management information system can basically achieve sharing, and the problems to consider include data conversion between heterogeneous databases, incremental data addition, data update synchronization, and the sharing of multiple different data sources, therefore, the research of heterogeneous database integration technology. In this paper, the method process of heterogeneous database integration is to specifically realize the process of data transformation and integration using XML Schema.XML Schema establishes a mapping mechanism between the datasheet definition of the relational database and XML data files, using which data in the relational database can be easily exchanged with data in the XML data file. This paper proposes a heterogeneous database integration model, constructs a hierarchical architecture including heterogeneous data source layer, intermediate data transformation and processing layer, interface service supply layer and client application layer; realizes the data transformation and integration process using XML Schema, designs XML-based data transformation function, including the structure of transformed data table and specific data transformation, designs incremental update synchronization, and realizes the release of heterogeneous database integration method in the form of service using Web Service technology. This paper adopts a service-oriented architecture mode, heterogeneous database integration specific method as Web service, in the client can realize heterogeneous database integration service function to avoid repeated input of the same or similar data, ensure data consistency; realize online analysis processing, data mining, make full use of data value, save investment, increase the life cycle of the existing management information system, and expand more application functions on the basis of the existing system.
Intelligent Systems Utilization in Recommender Systems: A Reinforcement Learning Approach

Recommender systems (RS) have been gaining momentum with the advent of digitalization of our daily lives, accordingly, companies seek to attract most customers in this environment. One way of attracting more customers by advertisements is through online ads that make use of click-through rates (CTR) for the ads to build efficient RSS. For the RSS, frequently utilized methods are collaborative filtering (CF), content-based filtering (CBF) along with one of the traditional reinforcement learning approaches. The objective of this paper is to determine the best online ad among multiple advertisements to show the customers by reinforcement learning (RL). By treating the problem in multi-armed bandits, we modeled the problem with Bernoulli distribution by means of obtained CTRs. The best ad was tried to be chosen by the Bernoulli bandit with three settings; A/B/n testing, epsilon greedy, and Upper Confidence Bound (UCB) methods. The results show the explorations’ contribution (with UCB and epsilon greedy) to the performance of the methods. Each method chose the same ad to show for online ads. UCB found the most preferable ad with a CTR rate of around 27.01%. It was followed by the epsilon greedy strategy with a CTR of around 25%. All the methods used determined the same ad alternative as the best according to the results obtained.
Design and Implementation of a Desktop Application for Consultation Centers for Staff, Information Regarding Training, Job Promotion and Transportation Routes, in an Automotive Electrical Harness Company

The use of Information and Communication Technologies (ICT) within the organizational context has revolutionized management and administrative thought, this is evidenced through various aspects, one is how human talent is managed (Riascos and Aguilera in Herramientas TIC como apoyo a la gestión del talento humano Cuadernos de Administración. Universidad del Valle Cali, Colombia, pp 141–154, 2011). The dissatisfaction of the workers of an electrical harness company located in Lagos de Moreno, Jalisco. For lack of timely information about their training, status of job promotions and transportation routes, was solved with the implementation of consultation centers (Kiosks) accessible 24 h a day, the relevance of developing an information system that will be linked to Kiosks, was identified, it was made with the V-Shaped Software Development Model. The updated information was generated a perception of equity, facilitating the integration of human resources in the management of the production process, due to the decrease in turnover, and a more satisfied and committed staff. A kiosk has been installed in each of the three locations of the company for its three thousand workers who have access to the module, regardless of the shift. They increased the perception of fairness by giving the areas involved updated information, thus avoiding employee discontent throughout the company.
Secure Deduplication

Data privacy and confidentiality become concerns for encrypted deduplication storage systems. The attackers intend to obtain the secret information that do not belong to them by performing side-channel attack and unauthorized access. Users usually encrypt data with their own keys to ensure confidentiality of outsourced data, which prohibits cross-user deduplication. It becomes an urgent problem to develop a secure and efficient deduplication system on encryption and key management. The rest of this chapter is organized as follows: Section 6.1 presents the related work of secure deduplication schemes. Section 6.2 describes the problems and the motivation of SecDep. Section 6.3 proposes the system architecture, and the design of user-aware convergent and multi-level key management. Section 6.4 presents the security analysis under the proposed threat model. Section 6.5 presents the experiment evaluation.
A novel feature extraction and mapping using convolutional autoencoder for enhancement of Underwater image/video

Marine resources known to human are very limited and as 71% world is surrounded by ocean, we are yet to discover the many of the species and the enriched resources. Often the Underwater scenery collected are poorly illuminated, degraded, and distorted due to light propagation model underwater, water molecules and impurities as well. Counting on to these factors images/videos collected in underwater environment are in need of enhancement. We propose a method of utilizing convolution autoencoder, which can be able to collect the features of underwater images and enhanced image and then the feature mapping of this can be used in testing of the other underwater images/videos. The method utilizes the technique, which combines benefits of unsupervised convolution autoencoder to extract non-trivial features and utilized them for the enhancement of the underwater images. In order to evaluate the performance, we have used both subjective as well as objective evaluation method. Evaluation parameters used represent the results of the proposed method are significant for enhancement of underwater imagery. With the proposed network, we expect to advance underwater image enhancement research and its applications in many areas like in study of marine organism, their behaviour according to the environment, ocean exploration and Autonomous underwater vehicle.
Using Book Dialogues to Extract Emotions from Texts

Detecting emotions from a text can be challenging, especially if we do not have any annotated corpus. We propose to use book dialogue lines and accompanying phrases to obtain utterances annotated with emotion vectors. We describe two different methods of achieving this goal. Then we use neural networks to train models that assign a vector representing emotions for each utterance. These solutions do not need any corpus of texts annotated explicitly with emotions because information about emotions for training data is extracted from dialogues’ reporting clauses. We compare the performance of both solutions with other emotion detection algorithms.
Case study: smart contract prototype utilising the blockchain to securely deposit NIST control findings

Security in online transactions is a critical component that cannot be overlooked in designing an accounting system for network-based trade. Previously, the challenge of double spending and the possibility for an external attack that could temper with records hampered the adoption of online transactions, additionally, the need for a trusted third party to validate transactions made over the networks made it too expensive to adopt such ideas. Thus, online transactions remained a dream for many. However, the introduction of blockchain and innovative contract technology has boosted their adoption. This document presents a case study report to develop a safe and secure system for government transactions using the mentioned technologies.
VASILI SESEMAN’S TRANSCENDENTAL THEORY OF KNOWLEDGE: BETWEEN PHENOMENOLOGY AND NEO-KANTIANISM

The article considers the theory of cognition of the Russian and Soviet philosopher Vasily Seseman (1884-1963) in its relation to the main philosophical orientations in early 20th-century: phenomenology, neokantianism, and intuitionism. Seseman’s theory of cognition is interesting today because, following the tradition of neo-Kantianism, it largely shares the principles and methods of phenomenology, poses epistemological problems that were not explicitly formulated by Edmund Husserl, and offers solutions that are relevant today. The article highlights a common thematic field combining phenomenology, neo-Kantianism, and intuitionism. This field is set by the initial subject-object cognitive attitude, the desire to identify the conditions for the possibility of cognition, the recognition of the presence of a non-linguistic level of knowledge. Moving in this unified theoretical cognitive context of the early twentieth century, Seseman offers his own solution to the following problems: defining the subject of cognition, developing the method of intuition in general and in relation to the contemplation of essence, distinguishing between objective and non-objective attitudes and using this distinction to describe different types of cognition, thematizing the irrational in cognition, and understanding the judgment and its role in the final formation of cognition. Seseman believes that the cognition of reality is preceded by the perception of its objects. He diverges from the Neo-Kantians, who claim that the objects of cognition are formed only in judgment, and holds a position than Husserl, according to whom we perceive the world around us already objectively. However, unlike Husserl, Seseman does not recognize the cognitive nature of perception and argues that knowledge begins with a reflexive fixation of the object of cognition. The cognition of an individual object is embodied in a judgment in which the relation of the object to its environment is fixed and the object is defined as a unique combination of universal properties. Finally, it is shown that the solution of epistemological questions inevitably leads Seseman to ontological issues.