Reviewerly/exHarmony huggingface dataset:
Effective Framework for Underwater Image Enhancement using Multi-Fusion Technique

Underwater environments are totally different from the atmospheric environments as the environments in underwater are often complicated and shortage of light due to its physical properties. Special cameras are used for underwater imaging are mainly used for observing the deep sea ground there exist many problems, the images are underexposed as the light transportation characteristic of water makes it difficult, the underwater images suffer by various effects and the images look hazy & blurred, they reduce clarity of image. In this paper, we present an efficient algorithm for underwater images enhancement by applying the enhancement technique in the original hazy underwater image and then calculating the white-balance and contrast enhancement technique and then calculate the weight-maps on both techniques and then finally fuse the images by fusion technique.
“Lock, Load, n’ Thank the Driver”: The Positive Influence of Prosocial Activity on Language in Online Social Groups

Social-psychological research aims to understand and improve human functioning in a wide variety of contexts. With research showing that trust, joy, and anticipation are among the most influential positive emotions in aspects of online communication, determining the environmental factors that may influence communication and interaction is of significant interest. This research aims to identify the ways prosocial actions influence language within an online social community. Using a longitudinal observational analysis of linguistic markers, an analysis was done on an online community, surrounding the game “Fortnite.” At different time intervals, the written dialogue was analyzed for psycholinguistic markers through LIWC to detect variance in tone within the community. Users were queried ( n = 9,037), filtered to meet the inclusion criteria (n = 7,221) and having their posts (n = 1,232,741) assigned to three cohorts, those of pre-prosocial, post-prosocial, and post-reciprocity, depending on the posting date. A statistically significant ( R 2 = .572) increase in positive emotion linguistic markers was detected in the data set after the prosocial action was added. A change in motivation did not reduce the use of positive emotion linguistic markers, contrary to what was expected. This research observes how individuals within online communities treat each other and that interaction can be influenced to improve the participant’s experience and the quality of dialogue. This research addresses how game design and human–computer interaction influence human communication and behavior. It supports that small changes to the real world have ripple effects in online communities for the better.
Automated classification of cancer from fine needle aspiration cytological image use neural networks: A meta‐analysis

Abstract Background The role of retrospective analysis has been evolved greatly in cancer research. We undertook this meta‐analysis to evaluate the diagnostic value of Neural networks (NNs) in Fine needle aspiration cytological (FNAC) image of cancer. Methods We systematically retrieved 396 literatures on cytodiagnosis of NNs from Cochrane, PubMed, and EMBASE. After screening, only six studies were included in meta‐analysis finally. Data was comprehensively analyzed by RevMan and meta‐Disc software. Results A total of 1165 cases were extracted from six articles. Among them, 593 cases were in the abnormal/positive group and 572 cases in the normal/negative group. The pooled estimates for the NNs cytology were Area under ROC curve (AUC): 0.99, Sensitivity: 0.85 (95% CI:0.82‐0.88), Specificity: 0.96 (95% CI:0.94‐0.97), Positive Likelihood Ratio (LR):18.43 (95% CI:6.83‐49.74), Negative Likelihood Ratio (LR): 0.06 (95% CI:0.001‐0.58), and Diagnostic odds ratio (DOR): 343.21 (34.41‐3422.77). Conclusions This meta‐analysis confirms that NNs Automated Classification algorithm can facilitate to some extent the FNCA diagnosis of cancer.
PIANI: An ontology-based platform for outdoor activity recognition and non-intrusive assistance to the elderly

In this paper, we introduce a Platform for Non-Intrusive Assistance (named PIANI), as an assistance platform for elderly people able to do activities in outdoor environments without strict supervision. PIANI includes an ontology used to characterize outdoor activities of interest (activities to be observed). PIANI also defines a risk level of the activity that an elderly person is currently doing out of his home by comparing such activity to its characterization. In addition, the proposed platform uses the smartphone of the person in order to collect geographic and time information, which is used by PIANI to infer activity risk and send alert notifications based on semantic knowledge base. An experimental test was developed as a proof of concept about the utilization of PIANI to identify outdoors activities of elderly people, compute a level of risk and finally send non intrusive alert notification to the user.
Arduino mobile robot with Myo Armband gesture control

In this paper we present our work regarding possibilities to control a mobile robot with the help of an innovative myoelectric sensing device called Myo, produced by Thalmic Labs. The proposed mobile structure is built upon the Arduino development board and it results in a tracked mobile robot. There are presented some design aspects that enable the system to be functional. Since Myo can interpret hand gestures, these are used to control the mobile robot, and described in the paper. The final goal of the project is to enable realtime control of the mobile robot using direct visual feedback. Also, an analysis of the system’s delay in command execution is presented in the paper.
Detection of Image Forgery

Digital Image Forgery can be done by deceiving the digital image to mask some meaningful or important data of the image.It is usually difficult to spot out the manipulated region of the original image.To sustain the uprightness and legitimacy of the image, the detection of forgery in the image is mandating.Acclimation of the modern way of life and advancement in photography gadgetry has made exploitation of digital image easy with the help of image editing software.Therefore, it is crucial to detect such image forgery operations in the images.The image forgery detection can be done based on object removal, object addition, unusual size modifications in the image.Images are one of the powerful media for communication.In this paper, a survey of different types of forgery and digital image forgery detection has been focused.
Maintaining Social Licence for Government Use of False Social Media Personas

Governmental collection of unprotected information from social media platforms via social media intelligence (SOCMINT) techniques enable the detection and prevention of unlawful and malicious activity for law enforcement purposes. Relatively new, these techniques have come under public scrutiny. Recognised as valuable tools for security, law enforcement and regulatory agencies, how government SOCMINT policies align with public expectations is less clear. This article addresses the gap by comparing New Zealand public expectations about the use of false social media personas as a SOCMINT technique with government policies. 248 individuals were surveyed, establishing initial understandings of public expectations. Findings were compared with policies of key oversight agencies – the State Services Commission and Privacy Commission. This article argues that to maintain social licence, governments using false social media personas need to appropriately balance public protection with personal privacy interests. Transparent policy frameworks are needed to maintain trust and confidence in SOCMINT governance.
Sociocultural approaches to mobile learning in bilingual teacher preparation: The benefits of SAML as both a strategy and belief

This article presents a cooperative inquiry into how teacher educators prepare bilingual teacher candidates to adopt sociocultural approaches to mobile learning in their field-based courses as a platform for engaging their culturally and linguistically diverse learner populations. A sociocultural approach to mobile learning (SAML) uses mobile devices to bridge students’ home and school lives in meaningful and relevant learning experiences. This study provides insight into how and why teacher educators should prepare bilingual preservice teachers to use mobile learning to address the cultural and linguistic needs of diverse learner populations. The authors posit that adopting sociocultural approaches to mobile learning is not just a strategy but a belief that teaching is about empowering students, being responsive to their cultural and linguistic needs, valuing their diversity, creating equitable access to technology, and making learning relevant and authentic – all of which can be facilitated through mobile learning. These beliefs that are facilitated by SAML are extended to the bilingual teacher candidates and ultimately onto their future students.
Big Data Preparation and Exploration

The realistic manner of extracting data from a huge source and processing it in an efficient manner is the real challenge of big data technology. The capability to transform this data to valid and precise data is a barrier. The poor decision-making due to wrong information and inefficient query processing will affect the accuracy and reliability of big data. The above consequence occurs because of lack of preparation of data for which the data to be processed needs to intensely explored. The chaos about the inconsistency of data can be diminished by the data cleaning step involved in data preprocessing. This also involves the data integration, data transformation, data reduction, and data discretization processes which make the graph of quality soar to its peak level. The functions Extract, Load, and Transform, which together are called as ETL, play a big role in online analytical processing system which helps the whole business intelligence ecosystem of big data in a better way. The fascinating correlation between data preprocessing with data wrangling is exemplarily defined with visual analytical tools and open source technologies like R, Python, etc. The major challenges of missing data imputation can be remedied by prediction models for both the categorical as well as continuous values. Proper identification and classification of the data, which are a necessity, can be done through proper security schemes involved in it. Schemes such as Panda Security Adaptive Defense 360 and context intelligence AU: Please revise this scheme name for clarity. can be put forward for the security of the data to a big extent. The truthfulness of data collection from the social networks and weblogs is a major threat in this technological world. The data veracity scheme involved in big data management is an exact solution for the above problem. Precision analysis is used to measure the veracity of data which can be attained with an Autoregressive Tree (ART) model for the analysis. This model is a baseline for predictive accuracy analysis for large datasets. The major role of big data technology comes in the advancement of prediction scheme in healthcare. The machine learning scheme involved in the medical field as a healthcare catalyst has turned round the clinical industry. Data science made a drastic change not only in medical field but also in business and enterprises for the better. The advantages of data preparation and exploration yield technological upgradation and are beneficial to world’s GDP rate too.
A 3D Convolutional Approach to Spectral Object Segmentation in Space and Time

We formulate object segmentation in video as a spectral graph clustering problem in space and time, in which nodes are pixels and their relations form local neighbourhoods. We claim that the strongest cluster in this pixel-level graph represents the salient object segmentation. We compute the main cluster using a novel and fast 3D filtering technique that finds the spectral clustering solution, namely the principal eigenvector of the graph's adjacency matrix, without building the matrix explicitly - which would be intractable. Our method is based on the power iteration which we prove is equivalent to performing a specific set of 3D convolutions in the space-time feature volume. This allows us to avoid creating the matrix and have a fast parallel implementation on GPU. We show that our method is much faster than classical power iteration applied directly on the adjacency matrix. Different from other works, ours is dedicated to preserving object consistency in space and time at the level of pixels. In experiments, we obtain consistent improvement over the top state of the art methods on DAVIS-2016 dataset. We also achieve top results on the well-known SegTrackv2 dataset.
Geochemistry and paleoenvironment of the phosphorites from the Ameki Formation, Niger delta, Nigeria

The phosphorites of the Ameki Formation occur as nodules, pellets as well as primary phosphatic shales and siltstones. Geochemical analysis of the phosphate samples was carried out to determine its chemical composition as well as its depositional environment. The methodology applied include XRF, INAA, XRD and thin section petrography using Polarizing Microscope. The XRF result identified CaO- P2O5- F as the major mineral group, SiO2, Al2O3, Fe2O3, MgO and TiO2, which show minor occurrences and Cr, U, Pb, V, Cu, Zn, Se and Cd that occur in trace amounts. The nodules and pellets are of medium to high grade (25- 34wt% P2O5) whereas the primary phosphatic shales and siltstones are of low to medium grade (4.5– 22wt% P2O5). The phosphorites comprise mostly of francolites. The mean index of refraction estimated by Becke-line method using Standard Polarizing Microscope gave 1.634 and1.636.XRD analysis yielded an average values of 9.243 (± 0.002) A° and 6.715 (± 0.002) A° for a and c crystallographic axes respectively with an axial ratio (c/a) of 0.726for unit cell parameter, suggestive of low degree of carbonate substitution. An increase in P2O5 content is found to be accompanied by increase in CaO, CO2 and F contents, but by a decrease in H2O, organic carbon, SiO2 and Fe contents indicative of amorphous solid phase of calcium phosphate. The phosphorite is interpreted to form under high biologic productive, shelf setting. High nutrient availability in the ancient sea is linked to upwelling along the West African Coastline during the Eocene.&#x0D; Keywords: Phosphorites; Geochemistry; Paleoenvironment; Ameki; Francolites; Nodules
COVID-19 PANDEMIC AND CENTRAL BANK DIGITAL CURRENCY AS THE FUTURE OF MONEY

Coronavirus disease, which was first detected in Wuhan, has spread globally, causing coronavirus pandemic in 2019-2020. Coronavirus disease has caused concerns about viral transmission through cash, reducing the use of banknotes and coins and causing changes in the way of people’s payment system. This brought the introduction of the “Central Bank Digital Currency” as a new digital payment system, which is thought to be resistant to a wide range of threats. This article provides a comprehensive overview of Finance and Investment readers about the Central Bank Digital Currencies (CBDC). The interest in Central Bank Digital Currencies’ arises from the developments that started with the 2008 crisis, such as the emergence of cryptocurrencies and the rise of digital transactions and reduced cash use. Some large Central Banks are actively investigating the introduction of sovereign digital currencies. In this study, how the Central Bank Digital Currency can transform all aspects of the monetary system and facilitate the systematic and transparent execution of monetary policy is examined through the examples of E-Peso and E-Krona.
Implementasi Algoritma C4.5 Mengetahui Penyebab Perceraian Dalam Pernikahan (Studi Kasus: Pengadilan Agama Medan Kelas I-A)

Divorce is one act that is hated by Allah. But it is permissible if a husband and wife cannot live together again, when both parties have fulfilled a deadlock in reconciling it will end with a decision that is divorced. Data mining is an automatic analysis of large or complex amounts of data with the aim of determining important patterns or trends. Data mining processing to classify the causes of marriage divorce using C4.5 algorithm by collecting data and classifying data using tree structure representation where each node represents the value of the attribute, the branch represents the value of the attribute and the leaf represents nodes that can search history data for classifying the causes of divorce based on previous traits, so that rules are found that are interconnected with each other. The tools used are Weka (The Waikato Environment for Knowledge Analysis) which is an open source application, Weka has 4 menu tools that can be used, including explorer, experimenter, Knowledgeflow and simple CLI. It has the advantage of many data mining and machine learning algorithms, the results of which are used to predict a set of data
Special Session: Blockchain Technology and How It Will Change Marketing: An Abstract

Blockchain was first described in 1991 by Stuart Haber and Scott Stornetta as a methodology to timestamp documents and became popular with the introduction of cryptocurrency in 2008. A blockchain can be both public and private and is often described as a special ledger (like a spreadsheet) with five distinctive features. (1) It is distributed, with no central database that if a copy is corrupted others can replace it. Although each participating member on the blockchain has access to the database, there is no single controller of the information. Every member can verify transactions directly without involving intermediaries. (2) Transactions are peer to peer. There is no central node for transactions. Each peer stores and forwards transactions to all other peers. (3) It is transparent, with all transactions visible in the blockchain. Members are given access to the blockchain and all nodes of the transaction. (4) It is immutable. Once a transaction is created in the chain and the accounts are updated, it cannot be altered. (5) It is based in cryptography, the connection of the blocks is cryptographically secured, and the last line of the block is added as the first line in the next block. Each block is connected to the preceding chain making the record chronological and permanent. Furthermore, the blockchain can be programmed to include rules that activate transactions between nodes. Blockchain technology expedites and solves many business challenges. For example, blockchain technology can be used for payment processing, fraud detection, supply chain management, and verification of ownership.
Sentiment analysis for opinion IESM product with recurrent neural network approach based on long short term memory

Industries Effort Small and Middle (IESM)is one of the economic backbone countries. The growth IESM increased 6% every year, pushed on its growth by many party, include government and private institution always conduct training and accompaniment effort, in this research we propose Recurrent Neural Network (RNN) based on Long Short Term Memory (LSTM) to classify opinion IESM product with comparison another models like Naïve Bayes, Support Vector Machine, K-Nearest Neighbor and artificial neural network sourced on dataset result survey square with focus on understanding of reviews a product classified for resulting feedback positive or negative, based on experiment result, RNN model and LSTM proposed produce level accurate better compared model Machine Learning (ML) basic, with 91.01% result accurate testing on model RNN+LSTM.
APPLICATION OF CRYPTOGRAPHY WITH DATA ENCRYPTION STANDARD (DES) ALGORITHM IN PICTURE

Cryptography is the science of maintaining data confidentiality, where the original text (plaintext) is encrypted using an encryption key to be ciphertext (text that has been encrypted). In this case cryptography secures data from a third party so that the third party cannot know the original contents of the data because the one who holds the key for encryption and decryption is only the sender and receiver. There are several cryptographic methods that are commonly used, one of which is DES or Data Encryption Standard. DES is included in the key-symmetric cryptography and is classified as a block cipher type
Issues Regarding the Optimum Tilt Angle of Solar Applications in Western Romania

The paper studies the influence of the tilted angle of the solar panel/collectors on the overall power conversion efficiency. There are calculated optimum tilt angle values for a solar system located in the western part of Romania. There is presented a comparative study between a fixed tilt system and a system with different tilting frequency using real radiation values and the general findings are reported in order to optimize the solar energy conversion systems.
STUDENTS’ SATISFACTION OF DISTANCE EDUCATION SERVICES IN THE ISLAND AREAS (A CASE STUDY AT UPBJJ-UT TERNATE)

This study aims to determine the level of student satisfaction in the islands regarding distance education services. The population in this study are all UT’’s students spreaded across various regions in the province of North Maluku. The sampling method uses simple random sampling, as many as 74 students. Data collection is carried out through interviews with respondents with questionnaire aids whose questions relate to UT's level of expectation and service quality. The results show that: (1) of all aspects of distance education services organized by UPBJJ-UT Ternate, all of them had been categorized as very satisfying, where the highest level of satisfaction was that of general information services by 101.28% or in other words had exceeded student expectations. While teaching material services, although still in the category of very satisfying for students, the percentage of satisfaction level is lower than other service aspects which is 95.76%. (2) From all aspects of distance education services organized by UPBJJ-UT Ternate, teaching material services still have a level of gap between expectations and valuations conducted by students.
Segmentation of color images using mean curvature flow and parametric curves

<p style='text-indent:20px;'>Automatic detection of objects in photos and images is beneficial in various scientific and industrial fields. This contribution suggests an algorithm for segmentation of color images by the means of the parametric mean curvature flow equation and CIE94 color distance function. The parametric approach is enriched by the enhanced algorithm for topological changes where the intersection of curves is computed instead of unreliable curve distance. The result is a set of parametric curves enclosing the object. The algorithm is presented on a test image and also on real photos.
Challenges and Opportunities When Integrating Artificial Intelligence in the Development of Library Management Systems

The digitalization poses new challenges, but also opens new opportunities to traditional libraries. This paper presents a Web client application for library management using latest advances in artificial intelligence (AI) in order to meet the needs of both the users and the library staff, so they capitalize on AI transformational search technologies to bring value to our communities. The starting point of the purpose of this application was to facilitate the process of reserving a book and at the same time it is desired to simplify the work of the library staff through various functionalities, such as searching for users or books using a QR code. However, due to the new opportunities opened by AI and machine learning (ML) technologies, all this data can be analyzed, and librarians can observe trends in reader’s choices, provide to the libraries the capacity to create an automated system of recommendations (RS), and also acquire new books which are of great interest to readers or give feedback to publishing houses.