Reviewerly/exHarmony huggingface dataset:
Modified skyline query to measure priority region for personal protective equipment recipient of COVID-19 health workers

The distribution of personal protective equipment (PPE) plays a vital role in meeting the needs of PPE in an area. This study aims to measure the priority of PPE recipient regions in West Java Province using a skyline query algorithm, namely Sort Filter Skyline (SFS). In this study, the SFS algorithm is modified to optimize the dominance measurement section. Regions that do not have hospitals will not be prioritized for PPE recipients. The preferences used in this study are maximum and minimum. The maximum preference rule is used for the number of ODP, PDP, positive and dead cases, while the minimum preference rule is used for the cured and distance attributes. The application of SFS for calculating priority regions has been successfully carried out by developing two models, namely MS1 using unmodified SFS and MS2 using modified SFS by adding a selection process for regions with no hospitals. The MS1 produces 21 skyline objects (55.55 %), while MS2 15 (66.66 %) skyline objects. The MS2 is faster than that of MS1 because fewer objects are being tested. The MS1 takes 0.0222 seconds, while MS2 only 0.0193 seconds.
Cryptanalysis of the GPRS Encryption Algorithms GEA-1 and GEA-2.

This paper presents the first publicly available cryptanalytic attacks on the GEA-1 and GEA-2 algorithms. Instead of providing full 64-bit security, we show that the initial state of GEA-1 can be recovered from as little as 65 bits of known keystream (with at least 24 bits coming from one frame) in time \(2^{40}\) GEA-1 evaluations and using 44.5 GiB of memory.
ALAT PENDETEKSI PENGECEKAN KEMATANGAN BUAH TOMAT MENGGUNAKAN ARDUINO DENGAN SENSOR WARNA

The development of increasingly sophisticated technology is now not only mastering the young but also has mastered all circles. and not only that technology is now not only used as a medium of information or receiving information but has been used as a business field, namely as online sales, education as a learning medium. Arduino is a new breakthrough in the world of microcontrollers. Arduino is open source and uses Atmel IC output as the main IC and has its own programming language similar to C language. Arduino types such as Arduino Uno, Arduino Nano, Arduino Mini and Mega. Tomatoes are a staple food and a source of agricultural income for the Indonesian people. Tomatoes can be found anywhere, including in the Riau Islands, Batam city. In shopping centers or traditional markets, before buying from farmers, traders check manually to determine the level of ripeness of the tomatoes. The best tomatoes can usually be seen from the color of the tomato skin. Tomatoes that are still fresh, which are ripe on the tree are usually reddish in color and tomatoes that are half-ripe and then left for a few days so that they are ripe are usually orange in color
Empirical View Of Financial Management Survey In Block Chain Technology Issues, Risk And Mitigation

A blockchain is simply a shared database of information or public ledger of all completed and shared transactions or digital activities between cooperating occurrences. Each transaction in the public ledger is confirmed by a majority of the participants within the device. Data cannot be removed once it has been input. The blockchain is a secure and verifiable record of every single transaction ever made. The most popular example of blockchain generation is Bitcoin, a decentralize dpeertopeer digital currency. Although the virtual foreign currency bitcoin is debatable, the blockchain technology that underpins it has performed admirably. The main hypothesis is that the blockchain creates a system for reaching a distributed consensus in the virtual online world. By developing an irrefutable file in a public ledger, participating entities may be certain that avirtual event occurred. It paves the way for the development of a democratic, open, and scalable digital economy from a centralised one. This disruptive period offers incredible prospects, and the change in this field has only just begun. The blockchain age is described in this white paper, as well as some intriguing specific applications in the monetary and nonfinancial sectors. We then research the difficulties ahead of time as well as the commercial opportunities in this critical age.
Regularized joint mixture models

Regularized regression models, such as the lasso and variants, are well studied and, under appropriate conditions, offer fast and statistically interpretable results. However, large data in many applications are heterogeneous in the sense of harboring distributional differences between latent groups. Then, the assumption that the conditional distribution of response Y given features X is the same for all samples may not hold (even approximately). Furthermore, in scientific applications, the covariance structure of the features may contain important signals and its learning is also affected by latent group structure. We propose a class of mixture models for paired data of the form (X,Y) that couples together the distribution of X (modeled using sparse graphical models) and the conditional Y | X (modeled using sparse regression). Both the regression and graphical models are specific to the latent groups and model parameters are estimated jointly (hence we call the approach regularized joint mixtures). This allows signals in either or both of the feature distribution and regression model to inform learning of latent structure and provides automatic control of confounding by such structure. Estimation is handled via an expectation-maximization algorithm, whose convergence is established theoretically. We illustrate the key ideas via empirical examples.
THE INFLUENCE FACTORS OF ELECTRONIC WORD OF MOUTH BEHAVIOUR IN FACULTY OF NURSING GARUT CLASS PADJADJARAN UNIVERSITY

Higher education in increasing competition needs to provide excellent quality services for students to college. Students satisfaction will be encouraged to disseminate their campus information through electronic word of mouth (eWOM). EWOM is a form of consumer willingness to voluntarily provide recommendations for others to buy or use products from companies through the internet. This research was conducted to analyze the quality of service, promotion, brand image and motivation towards eWOM. The research was quantitative research using a descriptive approach. The data were analyzed using SEM Lisrel (Structural Equation Modeling). This study was conducted of student from Faculty of Nursing Garut class who actively carry out lecture with total sample of 309. The findings of this research showed that there was a significant relationship between service quality on brand image, there is a meaningful relationship between the promotion of brand image, there is no significant relationship between service quality on eWOM, brand image has a significant to eWOM and motivation has a significant relationship to eWOM.
Next Word Prediction In Telugu Sentences Using Recurrent Neural Networks

Data that is collected from the social network is almost full of noise and extra characters. Popular social networks like Twitter, Facebook, WhatsApp, YouTube generate lots of data and preprocessing is the primary task to transform the messy data into useful or reliable data. The preprocessing step removes, replaces, modifies, and normalizes the collected data. It also fills the data with suitable words in incomplete sentences. In this paper, we address the procedure to predict suitable words in the incomplete sentence in the Telugu language.  Natural Language Toolkit, for example, Indic Language (iNLTK) supports the Indian language for processing 13 official languages in India. Here, Telugu is one of the languages that is supported by iNTK. The prediction of the next word can be implemented by using Recurrent Neural Networks, by predicting the next word in a sequence so that the number of keystrokes of the user can be reduced to save time. This approach can be used effectively for various NLP preprocessing methods, sentence auto-completion in Telugu.
The Effect of Work Discipline on Employee Performanceat Mc Donald's Branch Pondok Gede

It is an important part of a paper whose main function is to attract readers, managing editors, and reviewers. Therefore, abstract must be written attractive and can explain the entire content of the paper. It is better if the abstract is written after the paper is finished so that all aspects can be written Abstract writing is brief and clear about the problem so that abstracts should not be given quotes or theories. The essence of an abstract consists of the research objectives, research methods, and research findings. Research objectives can be written directly at the beginning of the paragraph or after a few sentences of the prologue. However, the methodology is an important part of a study because the success of the research depends on proper methods. The maximum number of words in an abstract is 250 words. In addition to words or terms in keywords, it serves to make it easier to classify the type of paper, so do not use phrases.
Exploring the Relationship between MIS and Decision-Making Process at Al-Hussein Bin Talal University

This study aims to identify the role of management information systems (MIS) towards decision-making in Al-Hussein Bin Talal University (AHU). To accomplish the objective of the study, the following hypotheses were formulated: There are NO statistically significant differences between MIS and the effectiveness of the decision-making process (DMP) at AHU. There are NO statistically significant differences in the attitudes of employees at AHU on the role of MIS in the effectiveness of (DMP) due to their demographic variables (gender, age, marital status, job experience, and scientific qualification). The study followed the analytical descriptive approach, a questionnaire was designed to collect the data, it was distributed to a sample of (180) managerial and academic staff of decision-makers at AHU with a recovery rate of (89%). The most important results are: There is a statistically significant relationship between MIS and the decision-making process effectiveness in AHU, The results also showed there are statistically significant differences between the role of management information systems in making decisions due to the variables (age, job experience, and scientific qualification). While there are no statistically significant differences of (gender and marital status) variables, the study recommend the need to increase the support of senior management at AHU for users of information systems, the need to provide training and development programs for them and the need to increase attention to MIS through regular maintenance, continuous development, protection of information, and building an integrated electronic system at the level of all Jordanian universities that guarantees participation as well as safe and effective information exchange between them.
Food recommendation system for the elderly

Making a food recommendation system for the elderly has the purpose to introduce nutritious food menus to guide nutritionally and promote the elderly to have good health. The system uses techniques that help guide food recommendations to help the elderly make decisions to select foods. There was an analysis divide by behavior given to the system by using a clustering algorithm. After that, the elderly or elderly caregivers are given a rating score using the Slope One Algorithm to predict which is improved with predict error value at 0.11-0.29 and recommend the food menu for the elderly in order to decide on the food that is good for the body by the system developed in the form of a Web application.
An Efficient CNN and BI-LSTM Model for Abnormal Event Detection in Video Surveillance

Abnormal event detection plays a complex and important task in intelligent transportation and Computer vision. At present, the existing abnormal event detection models based on deep learning mainly focus on data represented by a vectorial form, which pay little attention to the impact of the internal structure characteristics of feature vector. In order to address the above issues, we propose an abnormal event detection hybrid modulation method via feature extraction calibrating classification in video surveillance scenes in this paper. Our main contribution is to calibrate the classification of an abnormal event by constructing feature expectation subgraphs. First, we employ convolutional neural network and long short-term memory models to extract the spatiotemporal features of video frame, and then construct the feature expectation subgraph for each key frame of every video, which could be used to capture the internal sequential and topological relational characteristics of structured feature vector. This model included a pre-trained CNN for extracting spatio-temporal features from each individual frame selected from a series of frames, which is then passed to multi-layer Bi-directional Long Short-term Memory (BD-LSTM) that possesses the capability of accurately classifying the abnormal events in complex surveillance scenes of the road. Finally, the experiments and performance of frame level and pixel level values on a common UMN dataset are estimated and evaluated.
Using Augmented and Virtual Reality for teaching scientific disciplines

This paper aims at synthesizing the literature on the use of AR and VR for teaching scientific disciplines to identify strengths and weaknesses for student’s learning. Articles published in peer reviewed journals has been searched on Google Scholar from 2018. The results highlighted a great variety of studies’ methodology, field of applications, technology, target groups and outcomes. The growing interest in this topic is due to the emerging benefits for learning achievements, attitudes and motivations. Further studies are necessary to understand the type of technologies to be used in different contexts and to focus on learners’ characteristics, and its impact on learning outcomes. It is necessary to improve students’ and teachers’ digital competence, supporting them in designing educational intervention for the acquisition of scientific skills.
A Product Review System using Sentiment Analysis with Cuckoo Search and Deep Learning Technique

In last two decades, the explosion of e-commerce websites provide a lot of information to users for better analysis about anything. Millions of people express uninhibited opinions in terms of text about various product based on their features and e-commerce company status. This process forms an active feedback system which is of importance not only to the companies developing the products, but also to their rivals and several other potential customers those are trusted on online shopping. In this research, we present a method to analyze the product review based on available sentiment and model is known as a product review system using sentiment analysis with Swarm-based Cuckoo Search (SCS) and Artificial Neural Network (ANN) as deep learning technique. The objective of this research is identifying a set of potential features form text review data using the Lexicon-based feature extraction and SCS helps to select a set of optimal feature using the novel fitness function. Sentiment analysis in e-commerce company play a vital role to automatic extra the review polarity and arrange the review according to the polarity such as positive, negative and neutral. The extraction subjective information from reviews on the e-commerce site, social sites have gained greater attention from the data mining community but there management and fast response is still a big problem. To solve this problem, we present an intelligent system, which used a lexicon dictionary for text data polarity extraction and then SCS helps to select optimal feature form these and the experimental analysis shows that the effectiveness of system by comparing with state-of arts works in terms of performance.
봉오동ㆍ청산리 독립전쟁의 군사사학적 고찰

Until now, there have been tendencies in which independence movements have been understood as a history of struggles against the passive submission to the Japanese Empire. However, armed independence movements developed because of the ‘diplomatic independence movement’, which was a strategy to fight wars against Japan. For this, independence movement bases and independence groups were formed in the 1910s and armies for national independence were cultivated. The provisional government of Shanghai declared 1920 to be ‘the first year of war for independence’ and made it clear that actions against the Japanese army were war for independence. The procurement of armed power was most important in the development of such war of independence. In particular, the large number of weapons purchased from the Czech Legion played a decisive role in the victories of the 1920 war of independence in Bongo-dong and Cheongsan-ri.War of independence that developed continuously in resistance against the Japanese Empire were located at the center of all independence movements. Such war of independence led to the Righteous Army Movement, the war of independence of the army for national independence that developed in the Maritime Province and Manchuria, war of independence fought by the National Liberation Association in Manchuria during the late 1930s, and war of independence of the Korean Liberation Army and the Korean Volunteer Army in the 1940s. In particular, focus should be placed on the fact that armies for national independence with armed power in Manchuria developed the Anti-Japanese Armed Forces Struggle as a part of the war for independence around the 1920s. In other words, the Anti-Japanese Armed Forces Struggle in Manchuria was a war fought at the risk of lives and the history of the national independence army in Manchuria is the history of armed struggles and the history of war for independence. Therefore, in this article, war of independence that took place in the Bongo-dong and Cheongsan-ri battle areas was reexamined from military historical perspectives.
SMART HEALTH CONSULTING ANDROID APPLICATIONS

Health is a crucial part of human lives. Nowadays, healthcare is becoming vital each day, as there are lots of diseases that emerge around us. Technology is transforming the medical sector by massively impacting almost all practices and processes of medical professionals. Despite this, many of the people and medical staff still dealing with paper-based medical records and prescriptions while conducting treatment. When a patient wants to appoint any hospital or clinic, to carry previous medical reports or past prescriptions is becoming essential for them. It is necessary because the doctor gets an idea about the patient’s health status by referring to their previous medical histories, helping for better treatments and medications. However, patients cannot maintain every medical documentary for years. Conventionally, the doctor asks patients about their previous diseases, prescription, or medicine details orally, nevertheless it becomes difficult to get exact information from the patient. Sometimes, it becomes more important for the doctor to know about the medical history of a person so that they can provide suitable treatment with better clarity of that person’s health. Focussing on this, a smart medical assistant system is designed where doctors can record all prescriptions, treatment, or medical details of the patient on software instead of writing on a paper. All these records are stored in the central cloud and made visible to doctors as well as patients. Each patient has assigned a unique authentication card for maintaining the privacy of their medical history account. Doctors can access and update a patient’s medical history anytime and anywhere by logging into their account through a smartcard swipe. The system can avoid overdue to treatment decisions. Likewise, the system helps to keep transparency about medicines and treatment.
Provocations in Advertising: Social Precursors and Implications

Being fraught with risks, postmodernity forces social actors not only to rationalize their activities and search for fleeting opportunities but also resort to means of influence that help achieve their targets in the minimal amount of time. The field of advertising is not an exception, as copywriters are in constant search for tools that could help them in maximizing the impact of their advertisements and targeting their potential addressees.The paper aims to analyse the provocative aspects of advertising; its aim is to see how provocative techniques may be applied, what social implications they might have, and in which cases such advertising could prove to be dysfunctional in nature. It further considers the negative as well as the positive aspects of provocation in advertising.The methodology of the research is based on case study approach, analysis of creolized advertising materials, the explicit and implicit means of their influence in particular. The potential impact that may be exerted is considered through the analysis of semantics.The paper outlines the area of application of provocation and provocative strategies in advertising as well as the impact it exerts on the addressees in the process of social interaction. Subsequently, it sheds light on how provocation is used in modern advertising. It concludes that negative provocation may be used in advertising to manipulate the addressees’ actions and galvanize them into buying a product or a service, whereas some types of advertising such as social advertising may benefit its addressees and serve the purpose of resolving a number of social issues.
In Defense of the Learning Without Forgetting for Task Incremental Learning

Catastrophic forgetting is one of the major challenges on the road for continual learning systems, which are presented with an on-line stream of tasks. The field has attracted considerable interest and a diverse set of methods have been presented for overcoming this challenge. Learning without Forgetting (LwF) is one of the earliest and most frequently cited methods. It has the advantages of not requiring the storage of samples from the previous tasks, of implementation simplicity, and of being well-grounded by relying on knowledge distillation. However, the prevailing view is that while it shows a relatively small amount of forgetting when only two tasks are introduced, it fails to scale to long sequences of tasks. This paper challenges this view, by showing that using the right architecture along with a standard set of augmentations, the results obtained by LwF surpass the latest algorithms for task incremental scenario. This improved performance is demonstrated by an extensive set of experiments over CIFAR-100 and Tiny-ImageNet, where it is also shown that other methods cannot benefit as much from similar improvements.
Blockchain Technology Adoption and Implementation for Securing IoT Devices

The rise of connected world is a reality through Internet of Things (IoT) technology and is increasingly changing the way people live, communicate and work. Perhaps, for a continued support to be delivered efficiently and effectively in terms of the services IoT offers, there are some challenges which need attention. This is basically the security aspects pertaining to the data the IoT devices generate, collect and process. In the recent years, blockchain technology gained attention in cutting edge solutions based on securing IoT devices. However, it is observed that adoption of blockchain technology is limited in several countries. The proposed research aims to investigate potential barriers to adopting blockchain technology in smart city applications through a qualitative study. In addition, a stake algorithm to demonstrate the security aspect in IoT device is presented.
On the Reform of Higher Mathematics Teaching in Liberal Arts

Higher Mathematics; Liberal arts mathematics; Teaching reform; Innovative teaching