Reviewerly/exHarmony huggingface dataset:
Changes of Academic Career Mobility Policies in Universities in Northeast China

The free flow of university teachers can not only bring vitality and vitality to the academic ecosystem, but also the unity of the internal demands and external requirements of teachers' professional development.This paper mainly studies the development and changes of academic career mobility policy in Colleges and universities in Northeast China.With the help of the octopus data collector, this study carried out the main quantitative analysis of academic career mobility policy, supplemented by Excel 2013's later chart processing of the data.For the research problems, different research methods are used in this study.Through in-depth research on the relevant literature of academic career mobility, academic career mobility policy and policy text analysis, this study understands the research status of academic career mobility, policy and text analysis, defines the focus of this research, and seeks research methods and theoretical basis for the smooth development of research work.Due to the large time span and large number of academic career mobility policies involved in this study, in order to grasp the basic characteristics of the formulation of academic career mobility policies from a macro perspective and make a comprehensive quantitative analysis of the policy-making subjects, policy themes, policy objects and policy forms, this paper makes a secondary distinction between the elements involved in the policies, It constructs a structured coding and classification system of academic career mobility policy text.Among the policies related to academic career mobility issued in Northeast China, the university personnel system, high-level talent introduction policy, talent market policy and mobility supporting policies indirectly related to academic career mobility policy account for more, accounting for 25%, 24%, 22%, 16% and 11% respectively, and the overall proportion is 98%.It is of great significance to reduce the opportunity and time cost of academic career mobility, reduce the mobility risk of college teachers and increase the mobility income of college teachers.
"Decoding • Encoding" – an exploration of data narrative in Tibetan characters

Tibetan, as a communicative tool of the Tibetan people, it has a long history second only to Chinese in China. Tibetan is a beautiful and expressive language. It is difficult for us to come into contact with this ancient and mysterious writing in our daily life. How can we overcome the time-space distance and language barriers to establish cultural communication in the ever-changing modern society? This is the research background of our project. We created an interactive website, which driven by data narrative visualization and interactive experience, foucs on Tibetan characters. We tried to decode Tibetan artifacts, the writing patterns of Tibetan calligraphy and Tibetan poetry by data, reconstructing our understanding of the Tibetan culture, promoting and improving the mutual connection between different cultures.
Smart City Research Classification: A Systematic Literature Review

In the digital era, technological advances are always evolving as well as urban problems in a city.A smart city is an implementation in dealing with urban problems by providing public services.This public service is also related to one of the uses of applications that are integrated with ICT in public services.Smart cities also have various types of applications that can be used to provide services to the community.The progress of the internet of things and big data analysis has become the infrastructure in implementing smart city applications.This study aims to classify 25 cities that implement smart cities based on smart applications used using a systematic literature review method.With this research, researchers are expected to be able to identify the types of smart city applications that are classified in each city.
RANCANG BANGUN SISTEM PAKAR MENDIAGNOSA PENYAKIT OBSESSIVE COMPULSIVE DISORDER DENGAN METODE DEMPSTER SHAFER

Anxiety is a normal reaction to stress and can be beneficial in some situations. It can alert us to dangers and help us prepare and pay attention. Anxiety disorders differ from normal feelings of nervousness or anxiousness, and involve excessive fear or anxiety. Anxiety disorders can cause people into try to avoid situations that trigger or worsen their symptoms. There are several types of anxiety disorders, including Obsessive Compulsive Disorder. Obsessive Compulsive Disorder (OCD) is a disorder in which people have recurring, unwanted thoughts, ideas or sensations (obsessions) that make them feel driven to do something repetitively (compulsions). The repetitive behaviors, such as hand washing, checking on things or cleaning, can significantly interfere with a person’s daily activities and social interactions. This Expert system which implement Dempster Shafer Method can help anyone to make sure that they have OCD and need psichologist help to prevent this distress becoming worst.
Content Reinjection for Super Metroid

Academic procedural content generation (PCG) efforts often yield plausible game content but stop short of fully integrating it into the games that inspired it. This misses opportunities to discover game- and platform-specific constraints that were previously ignored in evaluations of playability (e.g. how invisible objects in a level design are used to explicitly control camera movement). Grappling with existing games can ensure that the PCG community is solving realistic problems, rather than convenient abstractions of them. In this paper, we use technical knowledge from the ROM hacking community along with the WaveFunctionCollapse example-driven generator to reinject controllably-generated level designs into the commercial Super Metroid ROM image (rather than a clone) for execution on physical Nintendo hardware. Our work charts a path for more realistic evaluation of the playability of generated content and highlights challenges for deploying generative methods. These challenges can spark a conversation about the ways that abstractions are used in PCG research.
Evaluation of the Text Input Performance of Touch-Based Smartwatches with Different Hand Postures and in Different Body Movements

Most of the previous studies on smartwatch input methods were conducted in a stable experimental environment (while the user was sitting and using comfortable hand postures), and there have been few studies on the characteristics of input methods using different hand postures and in different body movements. This study evaluated smartwatch performance with different hand postures and in different body movements and compared the result with the ZoomBoard performance. We collected 16 participants' smartwatch input data and analyzed their tapping behavior with four hand postures (index finger support [IS], no finger support, thumb and middle finger support [TMS], and thumb support) and in two different body movements (walking and standing). We studied the input accuracy and speed with different hand postures and the distribution of the touchpoints. The results indicated that IS has the lowest error rate and fastest performance when the user is standing, and TMS when the user is walking. Also, the different hand postures had different touchpoint distributions. Therefore, this paper provides design considerations for future research on human-computer interaction on ultra-small screens, especially smartwatches.
Real-Time Approach to Neural Network-Based Disparity Map Generation from Stereo Images

Generating depth maps using mono- or stereo- images is a topic of active research. This paper is dedicated to study of different methods of depth and disparity maps generating. It includes analysis of existing methods of depth maps generating and investigation and improvement of the real-time neural-network based method AnyNet. Our approach AnyNet-M related to the models which are make prediction stage-by-stage and increase quality of disparity estimation over time. Firstly, proposed method was tested on KITTI Stereo Dataset and custom OpenTaganrog dataset with images of 1242 × 375 resolution. The method was proved to be real-time with approximately 38 FPS using one TeslaV100 GPU. Secondly, quality of proposed model was tested and reached 5% of Average 3-Pixel Error on KITTI dataset. Finally, it was integrated to Robotic operation system for further use as part of the navigation systems of unmanned vehicles.
Fast Trajectory Planning for AGV in the Presence of Moving Obstacles: A Combination of 3-dim A* Search and QCQP

This paper concerns about the automatic guided vehicle (AGV) trajectory planning scheme. Nominally it should be formulated as an optimal control problem (OCP) and solved via numerical methods. The concrete procedures to solve an OCP numerically include discretizing it into a mathematical programming (MP) problem and solving the MP via an appropriate solver. However, most of the predominant MP solvers only derive local optima because global optimization takes too long. As the predominant MP solvers only find local optima, the solution quality relies on the homotopy class of the initial guess, i.e. the starting point of an optimization process. A* search in the abstracted x-y-time state space is adopted to find a suitable initial guess, which directly plans a coarse trajectory rather than a path. With the initial guess, an MP in the form of a quadratically constrained quadratic program (QCQP) is solved easily. Simulation results show that the average CPU time spent on the first-A*-then-QCQP method is only l.4035 seconds in MATLAB. Source codes are provided at https://github.com/libai1943/AGV_Motion_Planning_with_Moving_Obstacles.
A Robust BSP Scheduler for Bioinformatics Application on Public Cloud

Aligning genomic sequences is a simple method for handling and analyzing the information in Bioinformatics. Here, the author expresses the problems related to BLAST algorithm which is used for the alignment of the sequences of biological data as the data grows huge. The current BLAST algorithm provided by National Centre of Biotechnology Information (stand-alone) cannot address biological data dynamically that are in terabytes. Many schedulers have been proposed to address this issue. The existing sequencing methodology is the one which is based on Hadoop MapReduce framework that executes in a sequential manner by consuming more time and is cost expensive. Hence, the author in this paper has achieved the BLAST-BSPMAPREDUCE (Bulk Synchronization Parallel MapReduce) algorithm by further improving the BLAST (Basic Local Alignment Search Tool) algorithm that is on the basis of Azure Cloud principles to tackle the case of serial execution in Hadoop MapReduce framework. The exploratory study which has been presented in this work demonstrates that the proposed BSPMAPREDUCE has a better coordinating speed of bioinformatics genomic sequences and achieves much higher speed over existing Hadoop-BLAST algorithm and the experiment result shows that the proposed customized scheduler is highly robust and scalable.
Histogram of Gradient in K-Nearest Neighbor for Javanese Alphabet Classification

Purpose: The Javanese script generally has a basic script or is commonly referred to as the “carakan” script. The script consists of 20 letters with different levels of difficulty. Some letters have similarities, so research is needed to make it easier to detect the image of Javanese characters. Methods: This study proposes recognizing Hiragana's writing characters using the K-Nearest Neighbor (K-NN) method. In the preprocessing stage, the segmentation process is carried out using the thresholding method to perform segmentation, followed by the Histogram of Gradient (HOG) feature extraction process and noise removal using median filtering. Histogram of Gradient (HoG) is one of the features used in computer vision and image processing in detecting an object in the form of a descriptor feature. There are 1000 data divided into 20 classes. Each class represents one letter of the basic Javanese script. Result: Based on data collection using the writings of 50 respondents where each respondent writes 20 basic Javanese characters, the highest accuracy was obtained at K = 1, namely 98.5%. Novelty: Using several preprocessing such as cropping, median filtering, otsu thresholding and HOG feature extraction before do classification, this experiment yields a good accuracy.
A cross‐lingual secure semantic searching scheme with semantic analysis on ciphertext

Secure semantic searching can search arbitrary query words semantically related to keywords over the encrypted data. However, most of the current schemes perform the matching after query semantic expansion on the plaintext. The existing works rarely support cross-lingual searching that breaks the language barrier to allow a query issued in a lingual to retrieve the documents written in other languages. Meanwhile, most of the previous schemes are difficult to be applied to real-time applications because of their poor efficiency. This letter designs an efficient cross-lingual secure semantic searching scheme that performs semantic analysis, semantic matching, and relevance ranking on the ciphertext. The proposed scheme encrypts the language-aligned word vectors of the keywords, and further calculates the semantic similarity between the encrypted vectors to perform clustering for the encrypted keywords. Therefore, the scheme uses the encrypted language-aligned word vectors of query words to perform cross-lingual semantic matching only with the cluster centre keywords to get encrypted keywords semantically related to the query, instead of scanning all the keywords, thus significantly improving the search efficiency. The scheme also realises the ciphertext relevance ranking algorithm to rank the documents. Experimental results show the practicability of the proposed scheme.
The object detection system of balinese script on traditional Balinese manuscript with findcontours method

Lontar is a traditional Balinese manuscript with a Balinese script in it. Balinese traditional manuscripts can be more than 100 years old. The age factor of the Balinese manuscript has an impact on the Balinese script in it. Balinese script that has been written more than 10 years tends to be darker. This makes Balinese script not visible well, and this affects the image quality of the manuscript. This thing becomes the main issue in this research, Balinese script detection on Balinese manuscript images. the first of all is image processing using edge detection, canny and Sobel becomes the main algorithm of this process. After image processing, the Balinese manuscript will be processed with the findcontour method to detect an object that contains in it. The final process of this detection system is to separate detected objects into three main groups namely noise object, Balinese script object, and hole object. Application (Balinese script object detection system) is more accurate in detecting Balinese script objects in Balinese script under 1 year (new script), it tends to be more likely to find noise/dirt. This is because the writing of the lontar using a pencil first before using the knife media. This adds to the noise or dirt detected by the application The findcontour method can detect Balinese script objects with a detection result of 30% - 70% Balinese script objects.
Application design to help predict market demand using the waterfall method

Covid-19 has not been defeated make the economy unstable. The government increases purchasing power with a stimulus. The government's stimulus for PPnBM 0% of cars is a breath of fresh air. Sales rate increases. Even so, the ups and downs keep happening. Sales are unstable. In one to three months, five cars can be sold. It could also take 3 to 6 months, only 1 unit. Must make a strategy to avoid overcrowding of units. Like PT. Suka Fajar Ltd Medan. Companies engaged in the sale of Mitsubishi cars. As operating costs increase, management limits the acceptance of car shipments. This policy has fatal consequences. When consumers want to buy a particular car unit, it is not available. Incidents like this happened more than five times. The company's image is not good. Researched to design and build applications that can make predictions—collaborated with the linear regression. To be directed and sequential, the waterfall is used. Ensuring the application is suitable for testing with the black box. Research leads to the conclusion that the application is designed and built according to what is needed.
Real, Forged or Deep Fake? Enabling the Ground Truth on the Internet

The proliferation of smartphones and mobile communication has enabled users to capture images or videos and share them immediately on social networking and messaging platforms.These platforms are also used to manipulate the masses by performing social engineering attacks by sharing fabricated images (or videos).These attacks cause public shame, ethnic violence, and claim lives.With the rise of advanced image processing tools, the deep fakes are automated, and their implications are boundless.In this article, we discuss different types of modification of images/videos and survey the corresponding methods and tools.We also highlight the ongoing efforts to detect fake images and videos using advanced machine learning tools and fact-checking.Along with these tools, we also need different complementary approaches discouraging the production and propagation of manipulative forged images and videos on the Internet.This paper further emphasizes that we desperately need socio-technological solutions that empower end users with the right tools to make an informed moral decision while producing, uploading, and sharing media.Finally, supporting this, we discuss a holistic blockchain-based solution.
Exploring Quantum Computing to Revolutionize Big Data Analytics for Various Industrial Sectors

The pace at which data is growing is expected to outpace business organization’s ability to manage it with conventional computers by 2027. Even today’s big data technologies, such as Hadoop and MapReduce, will fail to keep up. There is a need to reconsider the approach to deal with such massive amounts of data. Quantum computing is one of the market’s potential solutions. This chapter delves into quantum computing with no prerequisites. It introduces basic quantum computing principles, discusses its potential to revolutionize various business sectors, provides an overview of quantum computing algorithms, software’s, and tools. Finally, this chapter outlines future research directions for quantum computing.
RETRACTED ARTICLE: Smart Pharma: Blockchain Enabled Internet of Things for Smart Pharmaceutical Traceability System

In the growth of the Pharmacy industry, the automation of smart traceability system is needed to prevent the fraud attempt. The proposed Blockchain integrated Internet of Things (BIoT) is constructed to provide the security in the industry by developing the Pharmaceutical traceability system which is capable of increasing the security and prevent the fraud attempts. The proposed system maintains the authentication, confidentiality and improves the data sharing and storage management in an efficient way. The monitoring system is developed to ensure the quality level of the traceability system with risk analysis and surveillance using the sensor network for communication. The performance analysis proves that the proposed system has improved performance compared to the other related techniques.
PENERAPAN DATA MINING DENGAN ALGORITMA NAIVE BAYES CLASSIFIER DALAM MEMPREDIKSI PEMBELIAN CAT

Companies need several types of communication technology that can predict customer purchase interest, the goal is that the company can properly consider product sales and determine the company's paint product supply. So far, the decision of the Home Smart sales manager has been made by looking at the closeness of the supplier relationship and how many sponsors are funding the company. So that sometimes the product cannot compete with other companies. The Naive Bayes classifier algorithm is one of the algorithms included in the classification technology. The application of the Naive Bayes method is expected to predict paint purchases from suppliers. From 60 paint purchase data tested with the Naive Bayes method, the results reached 80% of the accuracy of the predictions. Of the 60 tested paint purchase data, 48 paint purchase data were successfully classified correctly.
Pemanfaatan Free Apps dan Open-source Software sebagai Alternatif Pembelajaran Online SD Negeri 1 Terong Tawah

SD Negeri 1 Terong Tawah is an elementary school with an A accreditation and has implemented the 2013 curriculum (K-13). Along with implementing learning from home during the Covid-19 Pandemic, SDN 1 Terong Tawah has not implemented e-learning due to limited resources. Not all students have adequate devices to access the internet. This causes the learning process to be not optimal. In addition, the teachers of SD Negeri 1 Terong Tawah and academic staff are not familiar with online learning. In this case, the teachers are required to be able to manage creative content so that the online-based learning media that is applied can be easily understood and enjoyable to use, and no less important. The application is used, which must answer the problem, where every student does not all have a smartphone device. Through training activities on the use of e-learning that is open source, it is expected to be a solution that can answer the questions faced, where the applications developed are free media and can be opened on various internet-connected devices such as laptops/computers/smartphones, are web-based so that no installation process required.
CAN Data Compression Based on Sorting and Mapping Method

Various data compression techniques have been studied to reduce controller area network (CAN) bus overload due to the increase in the number of electronic control units (ECUs) in modern vehicles. In most CAN data compression algorithms, the differences between the current and preceding CAN messages are transmitted. The advantage of this approach is that very high compression efficiency can be achieved. However, the most serious drawback of this approach is that the effect of error in one frame propagates to all subsequent frames. In this paper, we propose a CAN data compression algorithm based on sorting and mapping method. The proposed method performs compression of the current frame without relying on the previous frame. Experimental results show that the proposed scheme can achieve the compression ratio of up to 53.4%.
Video game localization

Video games have become ever-present in digital life today with thousands of deeply invested players and fans. As a major form of entertainment and an impactful media, they influence and shape the global culture and way of life in contemporary digital society. Within a span of five decades, video games have evolved into a multi-billion-dollar industry, the economic and cultural globalization of which has made video game localization an essential part of the production cycle. As sophisticated technology-driven new media, video games have unique features that pose challenges to translators technically, linguistically, and culturally in the process of localization, which requires diverse approaches and multiple skills. As an emerging field of research in translation studies, video game localization has been drawing increasing attention. The past two decades, in particular, have delivered a proliferation of scholarly discussions that have significantly deepened the understanding of game localization both as a translation practice and a research domain. This chapter provides a snapshot of the current landscape in game localization research and highlights future directions.