Reviewerly/exHarmony huggingface dataset:
A Study on the Search for Key Technologies in E-commerce through Simultaneous Classification Network Analysis of Cooperative Patent Classification and Keyword Co-occurrence Analysis

Concerning the trend of online shopping for domestic and global markets, a curve of rapid sales growth every year can be found. The offline distribution market has recently been on a downward curve, and the proportion of online sales in the distribution industry is expected to continue to expand. Accordingly, e-commerce companies are implementing various strategies to expand the market and meet customer needs. For instance, Coupang’s core strategies are its signature delivery system called “Rocket Delivery” and expanding its infrastructure of logistics centers. To counteract Coupang’s market dominance, Naver has launched the “Naver Fulfillment Alliance” by partnering with key industry players. However, these market dynamics are Individual company strategies through research data and published reviews, and it is difficult to grasp the core technology strategy in the e-commerce field. Therefore, this study intends to derive and analyze core technologies using patent information, which is an important indicator of technological innovation in the domestic e-commerce field. To this end, data from 659 patents filed between 2001 and 2021 were sampled to conduct simultaneous network classification analysis using an advanced patent classification (CPC) system. In addition, the summary of the patent was analyzed using the text mining technique to analyze the simultaneous keyword appearance network. Through this study, seven technology group groups were analyzed in the e-commerce field, and product recommendation and shopping interface technology were analyzed as core technologies. As a result of this study, it is expected to help establish strategies and policies for the development of core technologies in the field of e-commerce.
PELATIHAN PENULISAN KREATIF MAHASISWA PROGRAM STUDI ILMU KOMUNIKASI UNIVERSITAS TEUKU UMAR

Productive writing is very helpful for learning and professional success. Creative writing is one of the activities that teaches writing skills so that the resulting writing becomes more interesting. This training was attended by students from the Communication Studies program at Teuku Umar University. Participants are expected to continue to improve their willingness and ability to write, opening up increasing opportunities to publish their creative writing both in print and online. This training was conducted in an interesting and fun way using a laptop and LCD media. This training uses the lecture method which is also equipped with a training conducted through persuasive presentation, discussion and practical exercises divided into three sessions namely Imagination, Fiction and Expression. After the training, there was an increase in the ability and willingness of the participants, especially in the area of ​​​​composing poems and short stories, which were written in a very short time.
A New Computational Approach to the Levenberg-Marquardt Learning Algorithm

A new parallel computational approach to the Levenberg-Marquardt learning algorithm is presented. The proposed solution is based on the AVX instructions to effectively reduce the high computational load of this algorithm. Detailed parallel neural network computations are explicitly discussed. Additionally obtained acceleration is shown based on a few test problems.
Optimalisasi Aplikasi Berbasis Web dalam Upaya Promosi dan Peningkatan Tingkat Hunian Kamar pada Santika Premiere Dyandra Hotel &amp; Convention Medan

Hotels play an important role in the tourism industry. Without a hotel, tourists would not be able to enjoy a comfortable vacation. This is because the hotel provides the services and other services you need for a comfortable stay. The hotel itself has the concept of a type of accommodation that is commercially operated, providing services such as accommodation, services and food and drink to the general public for a short stay. Medan has so many Star Hotel competitors that you need to develop an appropriate marketing strategy. Therefore, the right marketing strategy applicable in today's digital age is digital marketing, especially web-based applications. In this case, Hotel Santika Premiere Dyandra Medan also digitally marketed web-based applications and more. This is one of the mainstays for promoting and increasing room occupancy, which has been sluggish in recent years due to the Covid 19 pandemic. Web-based applications are called MySantika and MyValue. The benefits of the Internet and digital marketing are so great that you can benefit from the Internet in almost every area, including: B. Business sector through banking, insurance, travel, education, etc. Since the advent of the Internet, patterns of daily life have gradually changed.
Privacy of Personal Health Information (eHealth) and Covid 19 Pandemic: The Sri Lankan Experience

Privacy in relation to personal information is one of the most important facets of the concept of personal privacy as it demands that information that relates to a particular person shall remain private and secured. Covid-19 is a pandemic which affected the lives of almost all people in every corner of the world. The pandemic brought new challenges to governments, health authorities, and other private and public institutions so these authorities were compelled to introduce a number of control and preventive measures, in order to curtail the devastating impacts of the virus on public health. These measures include many preventive and control measures which have an invasive impact on the personal right to privacy. Sri Lanka also was also affected by the Covid-19 pandemic and the Sri Lankan Government imposed certain restrictions and control measures. However, the problem of whether the privacy of personal information was respected during in the context of Covid-19 is a question mark in the Sri Lankan context as there were a number of incidents where the privacy of personal information was risked. Sri Lanka does not have Constitutional protection for the Right to Privacy as a Fundamental Right under the Constitution of Sri Lanka or any Legislation on the Protection of Personal Information. In this context, this Article examines whether Sri Lanka has adequately responded to the need to assure the privacy of persons in collecting, accessing, sharing, and disclosing personal information in the context of the Covid-19 pandemic.
Detecting phishing gangs via taint analysis on the Ethereum blockchain

Blockchain technology has created a new cryptocurrency world and attracted a lot of attention. It also attracts scams, for example, phishing scam, a typical fraud, has been found making a notable amount of money in the blockchain ecosystem, which has a very negative impact. Considering the whole life cycle of a phishing scam, this paper proposes the concept of a phishing gang, that is, a set of accounts that serve for phishing activity and belong to the same entity on the blockchain. As phishers often use multiple accounts to commit phishing scams and money laundering, detecting phishing gangs in the blockchain ecosystem is a real and critical problem. To help deal with this issue, this paper proposes a method of detecting phishing gangs on the Ethereum blockchain. Specifically, we first construct a transaction network with a graph structure by mining the transaction record and the account labels of the Ethereum blockchain. Next, we propose the base and improvement methods of taint analysis, aiming to evaluate the taint score of each account by tracking the fund flow of phishing accounts. Then, with the results of taint analysis and some heuristic means, all accounts in the transaction network are divided into five categories. Based on this, we propose a heuristics algorithm for phishing gang detection. And we also summarize gang patterns and reveal money laundering in phishing activities. Experimental results indicate that the proposed framework can be used to build a uniform platform to monitor every account on the Ethereum blockchain for early warning of phishing scams and detection of the phishers' money laundering and cashing process.
Teaching Simple Structure by Using Snakes and Ladders Games to Improve Students’ Speaking Skill

This article discusses teaching strategies in teaching simple structure with snakes and ladders games to improve students’ speaking skill. Specifically, this article presents how teaching through games can improve students’ speaking by using snake and ladder games in simple structure. Teaching English by using board game materials (snakes and ladders) is great for learning English simple structure. This activity allows students to improve their understanding. This game is a simple and fun media for students. It can be found that from observation, questionnaires and writing and speaking exercises in learning English by using the ladder snake game. From the questionnaire data, it can be seen that all student answers that media board games can improve students' speaking ability. The sample of the research is class VII A MTS Sulamul Ma’ad Penujak in academic year 2022/2023 and there are 20 students in this class consisting of 7 male and 13 female. The data collection used direct observation techniques, measurement techniques and documentation techniques. The techniques of data analysis used descriptive and qualitativeIt was found that students enjoy, interesting, learn while playing, effective, understand, think creatively and remember the material. The use of the ladder snake game to teach speaking and writing competence improves students' ability in simple structure. This media is not only easy but also brings many advantages and effectiveness in teaching English. This was seen in the pre-test, cycle I, and cycle II in learning processes. It increased by 40% during the learning process from the pre-test to the Cycle I, taking the overall proportion to 85%. This may be because students are unfamiliar with the learning process by using the games of snakes and ladders. These were well implemented with an average category score of 75.72. The increase in student learning outcomes recorded a 10% increase from Cycle I to Cycle II, while the overall percentage of passing students increased to 85%. In other words, improving student learning outcomes at each level is a good improvement category with an average score of 80.33.Keywords: teaching, simple structure, snakes and ladders, fun, understanding
The impact of the abuse of administrative authority on the performance of municipal sector employees (An applied study on the employees of the Municipality of Asir region)

The study aimed to identify the impact of the abuse of administrative authority on the performance of employees in the municipal sector in the Municipality of Asir region. (SPSS), and the study population consisted of employees of the Asir Municipality Secretariat, whose number is estimated at (1900) employ , of which (249) are valid for statistical analysis, with a percentage of (77.81%) The study concluded: that the abuse of administrative authority leads to a low rate of job performance in the municipal sector, adding an Islamic dimension to administrative work, providing elements and value rules that will keep the administration away from abusing its authority. The study recommends: The administrative authority in the municipal sector should be committed to achieving the public interest, without violating the rights of employees, in line with regulations and laws, in order to avoid the suspicion of abuse of power. Holding training courses on a regular basis, which help in developing the administrative performance in the municipal sector and developing the performance of employees alike.
INVESTIGATING THE USE OF READING STRATEGIES AND ITS IMPACT ON READING COMPREHENSION AMONG INTERNATIONAL STUDENTS IN A MALAYSIAN PUBLIC UNIVERSITY

The aim of this study is to determine the extent to which reading strategies and English language proficiency influence reading comprehension among Chinese undergraduates studying abroad. In addition, the study also aims to determine the reading difficulties encountered by these students and to identify the effective reading strategies they employed to improve their reading comprehension. The quantitative information gathered via a questionnaire and a reading test. The SPSS (descriptive analysis) results indicate that reading strategies and language proficiency jointly account for the variance in the students' test scores. In addition to informing scholarly practises of academic reading, this research contributes to the development and teaching of ESL curricula by highlighting the essential components of an effective ESL academic reading module.
bigg2vec: Fast and Memory-Efficient Representation Learning for Billion-Scale Graphs on a Single Machine

Node embeddings obtained from information networks have been widely adopted for representing knowledge and driving various information retrieval and machine learning tasks. However, training node embeddings is computationally intensive, making it difficult to scale to larger graphs. Most existing works have addressed the scalability challenge by simply adding more hardware resources. For example, a common approach to speed up the training process is to distribute model computation across multiple machines and GPUs. This paper takes an orthogonal approach towards scalability by addressing the problem of computation complexity in training embeddings. We present bigg2vec for scaling up the embedding training process. bigg2vec introduces a novel polar coordinate-based system for internal representation and computation. It provides the following benefits: (a) It significantly reduces compute and memory requirements while improving embedding quality and (b) uses a novel graph organization to generate high-quality negative samples (this reduces the number of negative samples needed for training, which is especially beneficial f or skewed graphs). We have deployed bigg2vec to generate embeddings for multiple AI models within Visa. Our Global Personalized Restaurant Recommender System (GPR) is one such project that uses bigg2vec to periodically generate embeddings for over 450 million nodes connected by more than 3 billion edges. bigg2vec generates higher quality embeddings while training them faster than state-of-the-art methods on a single CPU-based machine.
Research on object detection for service robots based on image feature

Object recognition and location capture is one of the important functions of the service robot, and the accurate detection of the target is of great significance for the subsequent function expansion. This paper studies the three kinds of HSV, ORB, SIFT algorithm based on color features, shape features and gradient. According to different scenarios of target objects, the image features are extracted and object detection is carried out through different algorithms. Compared with the detection results, it is concluded that the selection of appropriate algorithms based on different features for object detection is more efficient, which lays a foundation for subsequent service robots to complete accurate grasping of target objects in complex indoor environments.
Local path planning for multi-robot sytems based on improved artificial potential field algorithm

In this paper, the local path planning of mobile robots is studied based on the improved artificial potential field algorithm. The principle of artificial potential field algorithm is explained, and several common shortcomings of traditional artificial potential field algorithm are explained. Accoding to the problem of unreachable target and local minimum in traditional artificial potential field algorithm, the repulsive force function is improved, and the method of resultant force offset is given. Finally, the improved algorithm is simulated in Matalb and compared with the traditional algorithm. Simulation results show that the improved algorithm obtained in this paper is more effective than the traditional algorithm.
A safe channel planning algorithm for unmanned boats for anti-mine tasks

When the surface ship team performs a voyage mission, it will face the threat of several mines deployed by the enemy. By performing the sea sweeping task with the pre-sequence surface unmanned boat, the position information of the mine target in the task area can be obtained. The safe channel planning is achieved furtherly, so as to provide stable and reliable multiple crossing channels for subsequent boat groups. In this paper, we completed the abstract modeling of the anti-mine scene combined with the actual sailing scene, and a channel planning algorithm based on depth-first search was proposed. At the same time, a channel evaluation scheme was formed. The feasibility and effectiveness of the method were verified through simulation experiments.
Multimodal Remote Sensing Image Match Based on Structure Tensor Feature Transform

Traditional feature matching methods like scale-invariant feature transform (SIFT) tend to work only on single modality images, but become poor on multimodal images due to nonlinear mapping between images. To cope with this problem, this letter proposes to use the invariance of structural information in images to detect and describe feature points, which is called structure tensor feature transform (STFT). First, STFT proposes anisotropic Gaussian directional derivative (AGDD) instead of first-order derivative for edge detection, which improves the ac-curacy and noise reduction ability of edges in multimodal images. Then, structural tensor feature decomposition uses each two edge images to decompose into a linearity map and an orientation map. Finally, sequence linearity maps and orientation maps are fused into a intensity map with rich structural information to obtain feature points and a feature description map. Experiments carried out on six types of multimodal images point out that the STFT can effectively overcome the difference in multimodal images compared to the state-of-the-art methods.
A Forensic Methodology for the Analysis of Twitter Application in Android Devices

Twitter is one of the major social networking platforms used by millions of users every day. On every second, around 6000 tweets are sent through Twitter. The forensic analysis of Twitter application is of utmost importance to crime investigators as it can contain a rich set of evidential artefacts. The physical acquisition of Android devices can unveil the forensic artefacts stored in the Twitter application database, but only the most recent tweets and messages. This paper introduces a new methodology to forensically extract Twitter cloud data using the access tokens present in Android devices. The tokens enable investigators to get authenticated access to Twitter cloud servers and further access to the entire data using Twitter APIs. The response data is encoded in JavaScript Object Notation (JSON) format, which is further analyzed to identify the attributes of each tweet object.
Knowledge Management System Pengajuan Nasabah Pembiayaan pada BJB Syariah

BJB Syariah has several work units, including branch heads, operational managers, back offices, tellers, customer service and marketing . In recording the submission of financing customers, BJB Syariah still performs the documentation using paper media so that the knowledge obtained is still difficult to process. It makes the customer data lost or not neatly arranged, leading to a relatively long period of searching the data. Therefore, it is necessary to have a system that can provide convenience in recording customer submissions in the form of a Knowledge Management System. The system is expected to produce information that is related to customers and can be documented as evidence of data storage in real time. The system development method used is Rapid Application Development (RAD) starting from the Requirement Planning stage to the Workshop Design stage. The design tool used is the Unified Modeling Language (UML). The system is made using software Preprocessor Home Page (PHP) as a programming language and MySQL as database management. The designing of this web-based knowledge management system produces reports containing customer data and reports on financing submission on a regular basis.
Sinhala Named Entity Recognition Model: Domain-Specific Classes in Sports

Named Entity Recognition (NER) is one of the crucial and vital subtasks that must be solved in most Natural Language Processing (NLP) tasks. However, constructing a NER system for the Sinhala Language is challenging. Because it comes under the category of low-resource languages. Therefore, the proposed approach attempted designing a mechanism to identify specific named entities in the sports domain. Firstly, a domain-specific corpus was built using Sinhala sport e-News articles. Then a semi-automated, rule-based component named as “Class_Label_Suggester” was built to annotate pre-defined named entities. After auto annotation, the outcome was further validated manually with a little effort. Finally, it was trained using the annotated data. Linear Perceptron, Stochastic Gradient Descent (SGD), Multinomial Naive Bayes (MNB), and Passive Aggressive classifiers were used to train the NER model. Though, the above Machine Learning (ML) algorithms showed approximately 98% accuracy, the MNB model demonstrated highest accuracy for the identified class labels of which, 99.76% for ‘Ground’, 99.53% for ‘School’, 98.55% for ‘Tournament’, and 97.87% for ‘Other’ classes. Additionally, high precision values of the above classes were 81%, 72%, 62%, and 98% respectively. An accurately annotated Sinhala dataset and the trained Sinhala NER model are main contributions of the study.
Key Technology of Bronze Restoration Based on Neural Network Algorithm – Taking He Zun of Baoji Bronze as an Example

Bronze relics are widely popular large-scale agricultural tools production ritual ware, as well as other ancient sacrificial and entertainment ceremonial articles in the ancient slave society of China at that time, representing and reflecting the advanced productive forces in ancient times. The production technology of bronze ware is a very important and time-honored treasure of Chinese bronze ware. However, these excellent human historical and cultural heritages with use age or traditional culture often pass away in historical time. Due to the influence of many human activities and some external natural forces at that time, bronze cultural relics have been eroded to varying degrees and are on the verge of complete destruction. Therefore, for bronzes, we should first take early protection measures and proper rescue, so that bronzes can be effectively and properly preserved and used for a long time. Based on this reason, this paper takes He Zun of Baoji bronze ware as an example and uses neural network algorithm to study the key technology of bronze ware restoration.
O espaço de possibilidades de jogo como objeto compartilhado entre game designers e jogadores

object between game designers and players