Reviewerly/exHarmony huggingface dataset:
Using SNS for loan review at the bank

Financial technology(FinTech) has rapidly affected how numerous financial services are provided presently. The efficiency of financial tasks is expected to give merits for both financial enterprises and consumers. Loan review is one of the most critical tasks for managing conventional banks. A bank evaluates the submitted documents and interviews by the applied enterprise. A large amount of time is spent on credibility evaluation, which is not an ideal situation for both parties. Therefore, this study proposes a more efficient credibility evaluation method by applying social networking services (SNS). The method mainly analyzes applicant information based on their relationship with credible words.
Development of standard loss analysis model using big data

The Republic of Korea Army conducts simulations during peacetime using ground operation resource requirements analysis model (GORRAM) to determine potential losses when at war based on the latest operation plan. Although war-game simulation can yield reliable results, it takes considerable amount of time and effort to build a database and generate scenarios. Therefore, a study is required to supplement the detailed war-game simulation method to quickly determine expected losses. Using data built-in GORRAM, we tested the significance of four factors using beta regression analysis. While multiple regression is most commonly used to model the causality, beta regression is a powerful method for modeling response variables in the (0,1) range, such as the loss ratio. We verified that three factors, namely ‘topography’, ‘operational posture’, and ‘friend/foe power ratio’ were related to loss. This study proposes a new method for calculating the expected loss in real-time, overcoming a limitation of existing war-game simulation methods.
Face Recognition Techniques and Implementation

Human face is multidimensional structure that conveys expression. Face recognition is one of the most essential techniques used these days for security purposes. Face recognition is capable of detecting human face. Face recognition has been a great tool used in various real-life scenarios like security systems, social networking platforms and numerous commercial areas. As compared to traditional ML algorithms, deep learning techniques have improved the performance and accuracy of image processing such as contrast adjustment, histogram and image blending. Face recognition is a method of perceiving the face of a person based on distinctive features. In this era of artificial intelligence, face recognition is one of the most popular among other biometric techniques. Other biometric techniques may fail due to some reason but human face recognition will be the same and work properly. Different approaches like statistical approaches, principal component analysis, local binary pattern, hybrid approaches, convolutional neural network and support vector machine are used to perform this task of face recognition. Finally, it is implemented using MATLAB based on eigenvectors.
How can blockchain revolutionize the health sector during Health Pandemics (Covid-19) in Kingdom of Bahrain

Blockchain is a sort of database that can be used to securely and permanently store data that is entered into the blockchain ledger and cannot be changed or destroyed. It's a database shared by various parties, including banks, insurance companies, hospitals, patients, and doctors. Because mistakes are made while moving information from one system to another, whether due to human error or malicious attack, every transaction in the blockchain ledger will have its own identification number and will use encryption for security and privacy. The research is a discussion about Types of blockchain technology's in the healthcare industry and points out three applications as An electronic health record that provides security and privacy, A platform called MiPasa uses smart contact tracing applying Hyperledger Fabric based framework, and the telecare system that applies sensors to store medical records and monitors patient's condition. The proposed applications are good examples that can be applied to the health sector in the Kingdom of Bahrain.
Handwritten Equation Recognition with Convolutional Neural Network for Second-degree Algebraic Equations

We present in this work a method for a handwritten second-degree algebraic equations’ recognition. First, we work with a residual convolutional neural network for individual symbol recognition. Next, we merge those symbols that exceeds some overlap threshold or to have double representation. Finally, we gather all symbols that belong to the same equation using an intersect detection algorithm, by tracing multiple lines with different slops.Furthermore, we prepare an image database with more than 2000 second-degree algebraic equations handwritten by many writers. Our result shows good performance compared with other works in literature.
Cultivation Strategies for Users of Smart Library in China

The smart library is a new concept and new practice of the transformation and development of the library. The article sorts out the concept evolution, constituent elements and characteristics of the smart library, and proposes that the realization of the library's smart service is positively related to the user's quality. Based on the development of the smart library in China, analyze current situation and practical dilemma of user cultivation, explore user cultivation strategies suitable for the development of smart libraries, enhance user cultivation awareness and improve public participation; differentiate user types and build a hierarchical cultivation system; integrate resources and expand cultivation models; cultivate smart libraries members, improve the quality of education; strengthen cooperation, build a coordinated development mechanism; evaluate the effect of cultivation, and focus on the dynamic development of user cultivation.
Conducting collaborative activities with level-based groups and its effect on student interaction and English learning

Interaction is a key means of mediating English learning. Focusing on the role of interaction in English learning, this study analyzed the effects of level-based grouping on learner-learner interaction and learning of key expressions required for conducting collaborative activities. To this end, a collaborative activity to promote learner-leaner interaction was devised using the learning contents at an elementary English level, and it was applied to 5th grade English classes. Thirty students carried out the collaborative activity by forming heterogeneous groups and homogeneous groups according to their level of English. The effects were examined by analyzing the amount and pattern of learner-learner interaction and identifying the degree of help in English learning. The main findings of this study are as follows. Learner-learner interaction occurred actively among elementary school students performing the collaborative activity, and it occurred in a way that helped them learn English more effectively.&#x0D; Learner-learner interaction helped the students to learn key expressions necessary for conducting the collaborative activity. According to level-based grouping, the effects of learner-learner interaction on the interaction pattern and English learning were different.
Achieving the Sustainable Development Goals (SDGs) and the Intricacies and Dynamics of Development Administration

Development administration is primarily concerned with the various strategies to achieve accelerated national development, especially in developing countries. One major instrument for achieving national development objectives is the development plan. The development plan stipulates development goals and targets, various policies, programs and projects, and finances to achieve the objectives of national development. However, despite all these efforts in Nigeria, it seems the level of underdevelopment is still high considering the various obvious statistics and realities on the ground. The paper examines the efforts of the government at national planning over the years and the achievement made so far on SDGs. It identified the intricacies and dynamism involved over time in the achievement of SDGs and as well proffers solutions for better management. Secondary data was derived from books, journals, online publications, and government official reports in gathering information for the paper. Content ana lysis was adopted in analyzing the data collected. The study concludes that attempts at achieving the various targets of the SDGs were not successful due to certain inherent peculiarities in Nigeria. The high level of poverty, unemployment, inequality and insecurity, low infrastructural development, and poor social services like education, health services, housing, electricity, etc. are peculiar indicators of these failures. The paper suggests among others: the building of institutional capacity and fit for governance, the need to confront the structural impediments confronting attempts at achieving public policy through a constitutional review, emphasis on infrastructural development adequate for achieving national development and enhancing technological development, and capacity building through a viable and efficient educational sector.&#x0D; Keywords: Development, Development Administration, Sustainable Development, National Development
Privacy challenges in cyber security against cybercrime in digital forensic. A systematic literature review in Pakistan.

Cybercrime is a criminal activity that either target or uses a computer network or a network device. IOT become the biggest domain in these days.it is difficult to adopt digital forensics tools in IoT but somehow digital forensics play an important role in cyber security of IoT. Privacy and security challenges are increased day by day in digital forensics. Cybercrime in cyber security is increased day by day in digital forensics. Privacy and security are relate with each other but difference is that privacy relate to any right you have to control your personal information and how it’s used. Lots of work has been done in security issue but less focus on privacy. In the recent year, privacy in cyber security is the biggest challenge against cybercrime in digital forensics. To overcome these challenges of privacy in cyber security we must have deep knowledge which threats and attacks are harmful of our network.in this article we discuss the current privacy threats and attack for cybercrime in digital forensics with the deep knowledge and proposed classification matrix and also define proposed system which control threats and attacks. To the best of our knowledge there is no survey on privacy challenges in cyber security against cybercrime in digital forensics.
The Detection and Prediction of Financial Frauds

This research aims to introduce and analyze different methods used to detect and predict financial frauds. Many methods and models were designed for preventing and detecting accounting frauds, by reviewing and discussing M-Score model, F-Score model, and Red Flags on existing fraud companies, the effectiveness of each method is analyzed and evaluated in this paper. According to the analysis of the three methods, M-Score Model and F-Score Model are effective regarding calculating the probability of financial frauds, and by using Red Flag analysis, some potential financial fraudulent behaviors could be detected by the investors. The evaluation of these methods could help investors to make better investing decisions since it enables a better prediction and prevention regarding financial frauds.
Aceh Store : Sebuah Sistem Informasi Geografis Penjualan Berbasis Android

The purpose of this study is to design an application that can help users find information on sales locations in Aceh. The several stages of work consist of; data collection, analysis, application design and design, implementation, and testing and evaluation. Based on the results of the activity of designing an android-based geographic information system for sales locations, Based on the results of the activities of designing an Android-based Aceh Store geographic information system, the author can conclude that; the system can be used to manage the results of data on food and beverage sellers in Aceh Province which is carried out online properly because the data is centralized on one server and at any time needed it can be searched easily, and the system can make it easier for users or visitors to get information about product sellers. which is specifically in Aceh Province.
The Forms of Politeness Applied by English Students in Communication to Their Thesis Advisor Lecturers Via WhatsApp

This research aims to determine the forms, scales, and factors of students' politeness in communication to their thesis advisor lecturers via WhatsApp. The research design was descriptive qualitative research. The subject of this research was 54 of 2017 English students' text messages to their thesis advisor lecturers who were selected from classes A, B, and C by using the purposive sampling technique. The data were analyzed based on theory forms of politeness by Kushartanti, scales of politeness by Leech, and factors affecting politeness by Brown &amp; Levinson's theories. From the findings of this study, there are four forms of politeness used by students, namely pronominal sentences, indirect sentences, opening sentences, and word appreciation sentences. The most widely used forms of politeness are opening sentences and appreciation words. Five politeness scales were also found, namely the cost and benefit scale, the optionality scale, the indirectness scale, the authority scale, and the last is social distance scale, where this scale is the most widely used. All politeness data are influenced by relative power and social distance, and there is no size of imposition politeness factor found. There are also two forms of impoliteness in this study, directness and without using the word appreciation and some students are classified as impolite based on the optionality scale. Students use all existing forms of politeness because they use Indonesian politeness forms and Indonesian culture, which considers these forms a sign that sentences in a conversation are considered polite. The form of politeness used by students is influenced by the politeness scale, that is social distance and vice versa. Based on the result, it can be concluded that most of the students have used politeness form when communicating with their lecturers through WhatsApp text messages.
Multi-spectrum Fusion Towards 3D Human Pose Estimation Using mmWave Radar

Range-Doppler Map (RDM) and Range-Angle Map (RAM) are two kinds of representation forms of spectrum data commonly used in human pose estimation with mmWave radars. It is often that using them separately will fail to work well when the reflection signals received are insufficient for reconstructing a non-destructive human pose. To remediate the destructiveness of human pose estimations with only RDM or RAM data, this paper will explore a novel paradigm of data fusion to take full use of RDM and RAM data in human pose estimation. In doing this, two issues arise: one is how to associate the features of the two spectrums and the other is how to remove redundant features. To address these issues, inspired by the structure of Transformer encoder, a novel multi-spectrum fusion method is presented, in which a cross-attention fusion mechanism is used to facilitate the corresponding velocity to angle at the same distance region but without introducing redundant distance features. Experiment demonstrated the effectiveness of our method.
Predicting the reaction efficiency of ginkgo biloba residues pyrolysis by using artificial intelligent algorithms under the background of Carbon Neutrality

Since the beginning of 2016, China’s annual emissions of herbal residues (HR) have exceeded 30 million tons. As a kind of solid waste, HR still contains a large amount of organic matter, which requires further industrial extraction procedure. Most of the existing studies are concerned with the feasibility of utilizing traditional Chinese medicine residues, meanwhile there are very few studies regarding the kinetics of pyrolysis in the process of resource utilization of traditional Chinese medicine residues. In this study, we comprehensively studied the kinetics characteristics of raw materials with various heating rates (10, 20, 30, and 40°C/min) using a synchronous thermogravimetric analysis, and we adopted Coats-Redfern model to study the thermal kinetics and thermal analysis of GBR. A novel method combining Genetic algorithm and Adaboost algorithm (GA-Adaboost) is proposed to predict the thermogravimetric curve of the raw plant material with respect to the heating rate and temperature. The experimental result shows that the activation energy of the raw material was determined by the Kissinger-Akahira-Sunose (KAS) ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"><mml:mrow><mml:mi>E</mml:mi><mml:mo>=</mml:mo><mml:mn>148.71</mml:mn><mml:mi>k</mml:mi><mml:mi>J</mml:mi><mml:mo>/</mml:mo><mml:mi>m</mml:mi><mml:mi>o</mml:mi><mml:mi>l</mml:mi></mml:mrow></mml:math> ), and the correlation coefficient was greater than 0.99. The optimal reaction mechanism determined by the Coats - Redfern method was random nucleation and subsequent growth. The GA-Adaboost model achieved good performance (with a fitting degree of 99.88% on training data, 99.80% on verification data, and MSE of3.4173) while predicting the pyrolysis process of ginkgo biloba residue. This study will provide theoretical basis and technical support for the efficient resource utilization of pharmaceutical residues and reduce environmental pressure.
Development of Sign Language Recognition Application Using Deep Learning

Deaf and dumb people use a sign language that can only be communicated through hand gestures to express their ideas and views. This coded language is mainly used by people who have speech and/or hearing impairment. The sign language is constructed by various movement of hands, arms, legs, or facial expressions to express their opinions. Meanings are communicated for every movement or position of gesture. Hand gesture plays a significant role to make mother tongue of impairment people for daily communication. The captured image feature can be extracted to translate the hand gesture communication to text\voice format to minimize the gap between the deaf and normal persons. This work considers the images of sign numerals to classify the numbers 0–9 and the alphabets for A–Z (including space).
Geological mapping by thermal inertia derived from long-term maximum and minimum temperatures in ASTER data

Thermal inertia is a geophysical quantity used to characterize geological features. Apparent thermal inertia (ATI) is an alternative quantity that can be derived from remotely sensed data. Calculation of the conventional ATI requires acquisition of a pair of daytime and night-time images taken within a short time interval, which can often be difficult to fulfil by satellite remote sensing due to orbit constraints. In this study, we proposed long-term ATI (LATI) as a new alternative ATI, taking advantage of the large ASTER data archive. Using the Cuprite area in Nevada, USA as a test site, ATI was calculated using an ASTER data pair that was obtained within 2 days. LATI was also calculated using a much more separated ASTER data pair: daytime on 5 August 2000 and night-time on 12 January 2012. These dates were chosen to represent the maximum and minimum yearly surface temperatures. There was a strong positive correlation between ATI and LATI. We can conclude that LATI is useful and superior to conventional ATI because the maximum and minimum land-surface temperatures tend to converge on certain values and can be used to characterize surface geological features with minimal effects from temporal atmospheric and environmental conditions. Thematic collection: This article is part of the Remote sensing for site investigations on Earth and other planets collection available at: https://www.lyellcollection.org/topic/collections/remote-sensing-for-site-investigations-on-earth-and-other-planets
Efficient Multi-Replica Cloud Data Integrity Checking Method Based on Enhanced PRF

Cloud storage is vital nowadays due to its scalability and availability. Clients can save their information on cloud without sustaining a local replica. To maintain privacy, the owners can confirm the integrity of the outsourced information. Users allow third-party auditors to prove the honesty of the data saved on the cloud server. Data integrity checking, plays a crucial role in safeguarding the user’s data, particularly when kept in public clouds such as Microsoft Azure. To ensure the availability of stored data, users prefer multiple copies of data at multiple locations. Honesty checking of multiple copies can also be guaranteed with integrity checking techniques. Even though various scholars have proposed several multi-replica truthfulness checking schemes, many possess computational overhead during honesty verification. In this paper, an enhanced puncturable pseudorandom function is proposed to bring down the third-party auditor’s processing overhead, as well as the cloud server during proof verification and proof generation of replica data blocks. The scheme supports dynamic updating of stored data in the cloud server with less communication overhead for insertion/modification and deletion. An indistinguishability obfuscation-based program is also used to preserve the confidentiality of the data stored.
Face Mask Detector Using Convolutional Neural Networks

A convolutional neural network (CNN) has one or more layers and is mainly used for image processing, classification, segmentation. CNN is commonly used for satellite image capturing or classifying hand written letters and digits. In this particular project, a convolutional neural network is trained to predict whether a person is wearing a mask or not. The training is done by using a set of masked and unmasked images which constitutes the training data. The performance of the trained model is evaluated on the test dataset, and the accuracy of the prediction is observed.