Reviewerly/exHarmony huggingface dataset:
A Compiler-Aware Framework of Network Pruning and Architecture Search for Mobile Acceleration

With the increasing demand to efficiently deploy DNNs on mobile edge devices, it becomes much more important to reduce unnecessary computation and increase the execution speed. Prior methods towards this goal, including model compression and network architecture search (NAS), are largely performed independently and do not fully consider compiler-level optimization which is a must-do for mobile acceleration. In this work, we propose NPAS, a compiler-aware unified network pruning and architecture search and the corresponding comprehensive compiler optimizations supporting different DNNs and different pruning schemes, which bridge the gap of weight pruning and NAS. Our framework achieves 6.7 ms, 5.9 ms, and 3.9 ms ImageNet inference times with 78%, 75% (MobileNet-V3 level), and 71% (MobileNet-V2 level) Top-1 accuracy respectively on an off-the-shelf mobile phone, consistently outperforming prior work.
Strategic Disclosure of Disruptions and Firm Stock Performance – An Event Study

Companies’ announcements are a signal to the market of their strategic decisions and intentions. Some firms create “strategic noise” to mitigate the effects of potentially negative disclosures by dampening any negative news with some important but unrelated information. This study examines the effects of the timing of supply chain disruption announcements on a firm’s stock performance. The results of our analysis are based on a sample of 29 companies which made announcements of supply chain disruptions that affected their operations between 2016 - 2018. We employ an event study methodology and examine the abnormal returns of companies in our sample to determine if the event – the supply chain disruption had an effect of the firm’s stock price. Our findings, although statistically insignificant, indicate that the timing of announcements does have an effect on a firm’s stock performance. We found that companies in our sample experienced positive abnormal returns relative to announcing an event and reporting a supply chain disruption. This study also examines whether the composition of a firm’s top management team (TMT) and its reputation in the market mitigate the effects of any announcements of a supply chain disruption. Our study contributes to the operations and supply chain management literature by advancing the integrated and contingency and signaling theoretical framework through which we examine these phenomena.
The Application of Computer-Assisted Teaching in the Scientific Training of Sports Activities

In view of the current sports training needs, the computer-aided teaching software Kinect is used as the image collector to collect moving images, and then the image is processed and feature extracted by the frame difference method and the Canny edge detection algorithm, and the horizontal line scanning algorithm is adopted. Complete the extraction of 25 different joint points of the human body. Experimental results show that the average correct recognition rate of the system for sports actions reaches 91.25%, and the correct evaluation rate reaches 95.9%, which can provide timely and effective feedback and evaluation, and play a certain role in sports training assistance.
STUDENT'S PERCEPTION OF TEACHER'S COMPETENCY IN LEARNING LOCAL LITERATURE IN ELEMENTARY SCHOOL

Teacher competence is related to the teacher's ability to design learning in the classroom. One material that has a high level of difficulty is local script material. In general, students have a low interest in learning literacy lessons. Based on preliminary research at one elementary school, it is known that students' interest in learning local characters is quite high. Armed with this initial study, it is necessary to conduct further research on how teachers design local script learning in the classroom so that learning is more interesting. This study aims to describe the competence of teachers in designing local script learning from the perspective of students. The research was designed in a quantitative descriptive form with the category of survey research. The instruments used are questionnaires and interview guidelines. The data obtained were analyzed using descriptive statistics. The research location is SDN Rada, Bima Regency. The subjects of this study were students of class V totaling 30 students. The results of this study indicate that teachers have good competence in the perspective of students. Students feel happy with the varied and fun learning models. Students' perception of teacher competence in teaching is what drives students' interest in learning to be higher.
Technology Disruption and Digital Colonialism

Chapter 6 discusses how past paths play a role in present-day questions related to the digital economy. This chapter examines how past legal and other institutions have influenced the diffusion of digital economy technologies and the tension between such technologies and existing institutions. This is an issue of global concern. African countries, however, have significant issues related to colonial legal and institutional overhang that cast a shadow over digital economy laws and policies.
RANCANG BANGUN APLIKASI EVALUASI DIRI SEKOLAH BERBASIS ANDROID (STUDI KASUS: DITJEN DIKDASMEN KEMENDIKBUD)

Abstract— School Self Evaluation application is expected to give solution for schools in the purpose of education quality assurance implementation in order to support the process of school activity. Since 2016, the application that had been developed is the web-based desktop application. This condition has some concequences,  and those are: the application has to be installed on the computer by every single school to make it operational, represented by school operator; the application can only be used by using computer desktop, and it cannot be accessed by mobile device such as smartphone and tablet; the application has requirements to be able to be accessed by some type of respondent, which are, teacher, students, and school committee. But with the existing application, that requirement cannot be fulfilled effectively because it can only be accessed from one computer, that is school operator’s computer; the application can only be installed in one computer desktop for every school, to prevent the unexpected outcome. According to the flaws and the requirements of the existing application, there should be a development of application that can answer the limitations mentioned above.
Innovative Processes in Vocational Education: Challenges and Opportunities

The system of higher education in modern conditions sets tasks related to increasing the efficiency of preparing students for professional activities. One of the ways to achieve these goals is to introduce innovations in the university. Innovative technologies in education make it possible to regulate learning, steer it in the right direction and also to provide training for modern specialists who are open to changes and innovations. The article provides an analytical review of the concept of “innovation”. The article studies the features of the use of this term in professional pedagogical education. The article considered current innovative processes in the vocational education system in the context of globalization. The essential characteristics of the concept of “innovation” are revealed. The authors found that at present in innovative activities the leading place is given to innovative thinking, the use of the capabilities of artificial intelligence, and the preservation of the identity of educational institutions.
Power Platform and Cognitive Services

Microsoft Power Platform is a collection of three products: Power BI to analyze and gain insights about your data, PowerApps to build apps on top of your data that users can interact with, and Power Automate to automate your business processes or workflows or build logic into your apps. All of the three Power Products are built to provide developers with a no-code or low-code experience, leveraging the basic building blocks and connectors that already exist on the platform.
Real Time Speech To Text Text To Speech Converter With Automatic Text Summarizer using Natural Language Generation And Abstract Meaning Representation

Due to extensive needs for growth in various sectors, which include software, telecom, healthcare, defence, etc., there is a necessary increase in the number as well as the duration of meetings, conference calls, reconnaissance stakeouts, financial reviews. The obtained reports of these play a significant role in defining the plan of actions. The proposed model is to convert real-time speech to corresponding text and then to its respective summary using Natural Language Grammar (NLG) and Abstract Meaning Representation (AMR) graphs and then again turned back the obtained summary to speech. The proposed model intends to achieve the task using two major algorithms, 1) Deep Speech 2, 2) AMR graphs. The speech-recognition model recommended has a speedup of 4x if the algorithm runs on a Central Processing Unit (CPU), and the use of particular Graphics Processing Units (GPUs) for running deep learning algorithms can give a speedup of 21x. The performance of the summarizer used is close to the Lead-3-AMR-Baseline model, which is a solid baseline for the CNN/Dailymail dataset. The summarizer we use scores ROGUE score close to the Lead-3- AMR-Baseline model with an accuracy of 99.37%.
PENDEKATAN MARKOV CHAIN UNTUK MENGANALISIS PERENCANAAN SUMBER DAYA MANUSIA DI KEPOLISIAN SEKTOR TAMALATE KOTA MAKASSAR

this research, an analysis of Human Resources planning in the Makassar City Tamalate Police Sector uses Markov Chain. The data used are sourced from secondary data in the Makassar City Tamalate Police Sector from the last two years period, from 2018 to 2019. The Markov Chain is used to find out transfers that occur between police positions with the first process being determining states, calculating inter-state probability values, forming a transition probability matrix, and predicting the number of police officers for the next six years. Based on the research conducted, it can be concluded that five states were formed, the ranks of the Second Police Brigadiers up to the Chief Police Brigadier are classified as Non-Commissioned Officers positions, state two the ranks of Second Police Inspector Adjutant up to First Pollice Inspector Adjutant are clarified as Warrant Officers position, state three Second Police Inspector up to Police Commissioner Adjutant are clarified Low-Rank Officers, four state Pollice Coommisioner are clarified of Mid Rank Officer, state five additional and reduction of Police Members. Based on the results of forecasting, the probability for the most Police Members in the year 2020 to 2025 is a member domiciled as a Non-Commissioned Officers, the probability of a large number of Non-Commissioned Officers is relatively stable at 0.54 from 2020 to 2024 and will decrease by 0.01 in 2025. Probabilities the number of Warrant Officers has increased quite dramatically, in 2020 amounting to 0.35 continues to increase until 2025 which is equal to 0.42. Whereas the probability for the number of Police Members to be Low-Rank Officers has decreased every year from 2020 to 0.08 to 0.03 in 2025. Then for Mid Rank Officers the probability for the number of Police Members to remain stable every year is 0.01. The probability of the number of Police officers in 2020 is 0.02 and in 2025 it is 0.01
An Improved Hyperspectral Image Super Resolution Restoration Algorithm Based on POCS

Super-resolution reconstruction is a rapidly growing research area in hyperspectral data processing. However, there exist some problems, such as edge blur, burr in the smooth area, subjective design of iteration times, et al. This paper analyzes the causes of blur and burr, and puts forward some countermeasures according to these problems. Firstly, gradient interpolation is used instead of the traditional nearest neighbor interpolation, which alleviates the edge blur to a certain extent problem, the projection operator calculated from the gradient map is introduced into the projection formula to solve the burr phenomenon in the smooth area. Then, the mean square error of the reconstructed image of adjacent iterations is used to measure the similarity of the reconstructed image between two adjacent iterations, which is used as the stopping criterion of iterations, avoiding the subjectivity of setting the iteration times artificially. Finally, the proposed algorithm is applied to every band of hyperspectral image. Experimental results show that the proposed algorithm has better performance than the traditional POCS algorithm in visual effect and quantitative criteria.
E-Voting With Hybrid Encryption Rsa Algorithm

Agriculture is said to be the backbone of the economy. Farmers toil hard with different kinds of crops to make good and healthy food for the country. There are more existing systems but uses outdated machine-learning techniques based on RNN( Recurrent neural network) which makes the process slower and more time-consuming. Here We are proposing a new CNN(Convolutional neural network ) based system which is fast and gives accurate results within seconds. CNN is power-efficient and is more suitable for real-time implementation. In this project, we use CNN algorithms which is very much better than the RNN algorithms used in the existing system.More parameters will be taken for the consideration of prediction in the proposed system. And we use Random Forest Regression, Multiple Linear Regression
Σχεδίαση και ανάπτυξη αμφίδρομων γεννητικών ανταγωνιστικών δικτύων υπό όρους για την ολοκλήρωση τρισδιάστατων σχημάτων

In a brief period, the rapid increase in interest in Computer Vision and Deep Learning has led to a plethora of different applications on text, images, and videos. Those applications range from simple problems such as “motion detection in static cameras” or “Spam Filtering” to more complex ones such as “Robot Object Grasping through Vision” or “Image Caption Generation.” With the expeditious development of Computer Graphics, and 3D models acquisition technologies, Deep Learning applications on 3D Object Models have attracted increased attention. Sensors can provide us with 3D data with rich geometry, shape, and scale information, and accompanied by 2D images, can grant us with a better understanding of a certain environment.Three-Dimensional Data can be represented in a variety of ways, one of the most commonly used being point clouds (PC), which preserve the primary geometric information in 3D space without any discretization. However, even Deep Learning on Point Clouds is still in its preliminary stages due to challenges encountered when processing PCs with Deep Neural Networks. One of the main challenges is that decent quality PC Models are hard to obtain and often miss parts of data. A way to solve this problem is to create a 3D Shape Completion Model capable of restoring those missing parts.In this dissertation, we will research a family of models, with a variety of applications in Computer Vision, called Deep Generative Models. Specifically, we will expand indepth on Generative Adversarial Networks (GANs) as well as Variational Autoencoders (VAE). GANs create new data based on a set of given training data, with which they have the same statistics, whereas VAEs ensure that their encodings distribution is regularized during the training so that the latent space is of sufficient quality, to generate new data. The main objective is to create a point-based shape completion network based on Deep Generative Models that can complete a partial scheme with reasonable results.
The AHP Analysis of University Marketing Communications Based on Promotion Mix: Evidence from Korea

Recently, Korean universities are experiencing difficulties due to the decrease of the school-age population caused by low birth rates and the situation is even more difficult for regional universities located outside Seoul and the metropolitan areas. Thus, universities have to carry out active marketing communication activities to secure their student quota. Universities have carried out various promotional activities, but such activities have been practiced based on available budget, without consideration of efficiency. Thus, this study utilized the Analytic Hierarchy Process (AHP) analysis to examine what type of marketing communication activities can be effective other than the traditional print and online advertisements, and examine the priorities of those activities. The results showed that of the first level factors, the importance weight of advertisement was highest followed by sales promotion, public relations (PR), and personal selling. Such results imply that although universities are placing great emphasis on personal selling activities such as admission briefing sessions in high schools and university admission exhibitions, such efforts should be placed on other activities.Of the second level factors, Out of Home (OOH) advertisements, advertorials, and university posters posted in the walls of corridors and stairways of high schools showed high importance weight. This result implies that a sufficient amount of budget should be assigned to such fields. Also, television advertisements were analyzed to be less suitable due to their high expenses. Lastly, university posters posted in high schools showed the highest importance weight in the sales promotion field. Moreover, these university posters provided in high schools showed the highest importance weight after online advertisements in the total ranking of the second level factors.
Quantum Logic in DNA

We are here to consider the DNA molecules' spin system to consider when the antiferromagnetic spin chain is formed by the top remains’ axis. It ap-pears that the turning and twist are not two separate entities, not the one the other on the set. This formality assistances us in depicting the thermodynamic entropy as entanglement entropy, and hence the concurrence of two-set entanglement is appraised for transverse Ising model, and antiferromagnetic chain for the assess-ment is that the other methods are to obtain agreements with the excellent deal appeared to be.
Government Chatbots now a Necessity for States, Cities, Counties

Before COVID-19, a few leading governments were dabbling in chatbot technology, using AI to address common resident queries. In 2021, it's hard to imagine government doing the people's business wit...
Diseño e Implementación de Kits para la Experimentación de Biotecnología en el Hogar (HomeLab)

With the situation of the COVID-19 pandemic, professors had to accelerate their adaptation to the use of digital and remote media to continue with the education of students. Online teaching lab courses present great challenges, as many lab courses are designed to learn from hands-on and real-world exploration. Laboratory courses generally focus on deepening understanding of content and developing skills in experimental techniques. Added to this, the possibility of providing the experience of executing protocols and manipulating equipment, can hardly be achieved with a completely digital model. To promote better learning of laboratory subjects, kits were developed by professors to conduct laboratory practices at home. The students had the opportunity to execute biotechnology protocols following instructions and remote guidance from their professors. Conducting experiments at home,had a high acceptance rate as an efficient tool to learn various skills compared to digital tools.
Pelatihan Menulis Cerpen Sebagai Penguatan Program Literasi Pada Siswa Smp Kanzul Mubaarok Kota Bekasi

Writing was an ability that needs to be developed from an early age. The ability to write was still an obstacle for teachers and students. This was due to less than optimal reading interest. This activity took place from June to May 2021 . Activity aimed to produce a collection of short stories from the students of SMP Kanzul Mubarok. Activity was attended by 20 students and 3 teachers of SMP Kanzul Mubaarok Bekasi City. The result of the activity was the publication of short stories with characters made by students. The title of a collection of short stories created by students entitled: Can I stay, rays of guidance from the eastern horizon, from Jogya to Malaysia, and true friendship, Sabrina: a glimpse of a travel story. The final result was not everything, students' ability to write must be continuously honed and trained so that the ability to choose diction, grammar and imagination was strong. It could be concluded that students' writing talents and interests had different levels. In writing, students had different abilities, so that teachers must be able to accommodate these various abilities. Students were more excited when their short stories could be published, and given an ISBN
VIRTUAL REALITY BASED ANDROID APPLICATION FOR SPECIAL CHILDREN

Dyscalculia is a hidden neurological disorder in which a child feels difficulty while learning mathematics. Several Virtual reality based applications for cognitive learning for a special group of users have been developed and effectively used to learn complex concepts of various subjects. In our proposed virtual reality android based application we try to combat the issues of dyscalculia children to learn and understand basic of place value of digits and basic mathematical operations in an effective and immersive interactive environment of Virtual reality based class room.
Design of Digital Infinite Impulse Response Filter Based on Artificial Fish Swarm Algorithm

Filter design is an indispensable part in the field of digital signal processing technology. With the continuous improvement of signal processing requirements, the calculations required for digital filter design are becoming more and more complex. Therefore, using biological intelligent optimization algorithms has very important practical significance in improving the quality of digital filters design. According to the characteristics of the infinite unit impulse response filter, taking the coefficients of the system function as the optimization variable, this paper constructs the mathematical optimization model of the digital filter design, which takes the minimum square error of the system function of the design filter and the ideal filter as the optimization the goal. The artificial fish swarm algorithm is used to solve the optimization model of the digital filter, and the realization process of the artificial fish swarm algorithm to solve the filter optimization model is given. We use MATLAB software to simulate, compare and analyse the influence of artificial fish swarm algorithm parameters and filter parameters on the design results. The experimental results show that the artificial fish swarm algorithm can effectively design the digital filter, and the amplitude-frequency response curve of the optimized filter is roughly the same as that of the ideal filter.
ANALISIS PEMEROLEHAN BAHASA PADA ANAK USIA DINI DALAM TATARAN FONOLOGI

Language is a symbol of sound used by humans to interact with other humans which contains meaning. Language is acquired when the child is still a toddler. Language acquisition is acquired naturally when the child learns the first language. This study aims to describe vowels and consonants in early childhood at the phonological level. Many children at an early age still have difficulties or are not clear about pronouncing vowels and consonants. The method used in this study is a qualitative descriptive method which aims to describe the acquisition of language in early childhood at the phonological level related to vowels and consonants, while the technique used in this study is that the researcher makes observations then the researcher records what the child is saying. After that, the researcher wrote the utterance to be researched. The results obtained in this study are that there are difficulties in the vowel phoneme /ә/ and consonants /r/, /s/, /k/, /c/, /η/, /q/ and there are many simplifications of words such as [sepeda]. becomes [pedah], [becak] becomes [ta] changes consonant / c / to / t /, [tangan] becomes [anan], [motor] becomes [otol], [bunda] becomes [nda].