Reviewerly/exHarmony huggingface dataset:
Design of a Hybrid Recommendation Algorithm based on Multi-objective Collaborative Filtering for Massive Cloud Data

The current recommendation technology has some problems, such as lack of timeliness, the contradiction between recommendation diversity and accuracy.In order to solve the problem of lack of timeliness, the time factor is introduced when constructing the self-preference model.The cold start problem in the collaborative filtering algorithm is solved by the hybrid similarity calculation method, and the potential preference model is constructed.The two are fused to obtain a hybrid recommendation algorithm to improve the recommendation performance of the algorithm.For the problem of multi-objective contradiction, the NNIA algorithm is used to further optimize the candidate results of mixed recommendation, and the final recommendation list is obtained.Through verification experiments, the results show that the recall rate and accuracy of the fused preference model are better than those of the non-fused model, and the accuracy is 9.57% and 8.23% higher than that of SPM and PPM, and the recall rate is 9.97% and 7.65% higher, respectively.CBCF-NNIA algorithm has high accuracy and diversity of recommendation, and can provide users with rich and diverse text content to meet their own needs.
Unsupervised Feature Learning Methodology for Tree based Classifier and SVM to Classify Encrypted Traffic

Presently, sample social applications have emerged, and each one is trying to knock down the other. They expand their game by bringing novelty to the market, being ingenious and providing advanced level of security in the form of encryption. It has become significant to manage the network traffic and analyze it; hence we are performing a network traffic binary classification on one of the globally used application – WhatsApp. Also, this will be helpful to evaluate the sender-receiver system of the application alongside stipulate the properties of the network traces. By analyzing the behavior of network traces, we can scrutinize the type and nature of traffic for future maintenance of the network. In this study, we have carried out three different objectives. First, we have classified between the WhatsApp network packets and other applications using different ML classifiers, secondly, we have segmented the WhatsApp application files into image and text and third, we have incorporated a deep learning module with the same ML classifiers to understand and boost the performance of the previous experiments. Following the experiments, we have also highlighted the difference in the performance of both tree-based and vector-based classifiers of Machine Learning. Based on our findings, XGBoost classifier is a pre-eminent algorithm in the identification of WhatsApp network traces from the dataset. Whereas in the experiment of WhatsApp media segmentation, Random Forest has outperformed the other ML algorithms. Similarly, SVM when clubbed with a Deep Learning Auto encoder boosts the performance of this vector-based classifier in the binary classification task.
Software Effort Estimation through Ensembling of Base Models in Machine Learning using a Voting Estimator

For a long time, researchers have been working to predict the effort of software development with the help of various machine learning algorithms.These algorithms are known for better understanding the underlying facts inside the data and improving the prediction rate than conventional approaches such as line of code and functional point approaches.According to no free lunch theory, there is no single algorithm which gives better predictions on all the datasets.To remove this bias our work aims to provide a better model for software effort estimation and thereby reduce the distance between the actual and predicted effort for future projects.The authors proposed an ensembling of regressor models using voting estimator for better predictions to reduce the error rate to over the biasness provide by single machine learning algorithm.The results obtained show that the ensemble models were better than those from the single models used on different datasets.
Realizing the Quantum Relative Entropy of Two Noisy States using the Hudson-Parthasarathy Equations

The idea of noisy states can be derived through a quantum relative entropy over a given time period and construct the average value of at time based on the system variables.A random Hermitian matrix is used to represent the quantum system observables with BATH states.The Hudson-Parthasarathy (HP equation) context for stochastic processes allows us to simulate quantum relative entropy using quantum Brownian motion.The Sudarshan-Lindblad's density evolution matrix equation was already derivable in generalized form in my previous work.This paper's goal is to illustrate how the HP equation may be used to estimate the density matrix for noise in a perturbed quantum system of a stochastic process.The last stage involves using MATLAB to estimate and simulate a random density matrix and measure the quantum average at various times.These formulas would be helpful in determining how sensitive the evolving/evolved states are to changes in the Hamiltonian of the noise operators in a sensitivity/robustness study of quantum systems.
An OCR Engine for Printed Receipt Images using Deep Learning Techniques

The digitization of receipts and invoices, and the recording of expenses in industry and accounting have begun to be used in the field of finance tracking.However, 100% success in character recognition for document digitization has not yet been achieved.In this study, a new Optical Character Recognition (OCR) engine called Nacsoft OCR was developed on Turkish receipt data by using artificial intelligence methods.The proposed OCR engine has been compared to widely used engines, Easy OCR, Tesseract OCR, and the Google Vision API.The benchmarking was made on English and Turkish receipts, and the accuracies of OCR engines in terms of character recognition and their speeds are presented.It is known that OCR character recognition engines perform better at word recognition when provided word position information.Therefore, the performance of the Nacsoft OCR engine in determining the word position was also compared with the performance of the other OCR engines, and the results were presented.
A Study on Distance Personalized English Teaching Based on Deep Directed Graph Knowledge Tracking Model

Despite the continuous development of online education models, the effectiveness of online distance education has never been able to meet people’s expectations due to individual difference of learners. How to personalize teaching in a targeted manner and stimulate learners’ independent learning ability has become a key issue. In this study, the multidimensional features of the learning process are mined with the help of the BORUTA feature selection model, and the DKVMN-BORUTA model incorporating multidimensional features is established. This optimized deep knowledge tracking method is combined with graph structure rules. Then, an intelligent knowledge recommendation algorithm based on reinforcement learning is used to construct a fusion approach-based model for distanced personalized teaching and learning of English. The results show that the research proposed fused deep-directed graph knowledge tracking with graph structure rules for remote personalized English teaching model has the lowest AUC value of 0.893 and the highest AUC value of 0.921 on each dataset. The prediction accuracy of the research model is 94.3% and the F1 score is 0.92, which is the highest among the studied models, indicating that the proposed model has a strong performance. The fusion model proposed in the study has a higher accuracy rate of knowledge personalization recommendation than the traditional deep knowledge tracking model, and it can help learners save revision time effectively and improve their overall English performance.
EFFECT OF ABSORPTION AND UTILIZATION OF INFORMATION TECHNOLOGY AGAINST THE TEACHING AND LEARNING PROCESS IN PRIVATE ELEMENTARY SCHOOLS

The purpose of this study was to determine the effect of absorption and utilization of information technology on the teaching and learning process. The data used in this study is primary data obtained from distributing 91 questionnaires and returning 74 elementary school students. The data analysis method uses the Package for the Social Sciences Statistical analysis using IBM SPSS version 16 software. The results show that absorption does not have a significant effect on the teaching and learning process and the use of information technology has a significant effect on the teaching and learning process. This concludes that the use of information technology is carried out to support teachers and students in increasing efficiency and effectiveness in learning and has a positive impact. Absorption and Utilization of Information Technology collectively have a significant effect on the teaching and learning process.
News from the Field

2023 I Love My Librarian Award recipients New from ACRL—Undergraduate Research &amp;amp; the Academic Librarian, Volume 2 JSTOR, university press partners announce Path to Open Books pilot Bloomsbury premiers opera collections New from ACRL—Thriving as a Mid-Career Librarian: Identity, Advocacy, and Pathways MIT Press adds monographs to D2O Kanopy launches academic library subscription model ALA Public Policy and Advocacy Office names senior policy advisors
Computer modeling of physical phenomena

This article presents aspects of the use of Information Technology in physics lessons, in particular, the work of students with computer models. This work helps to increase students ' interest in studying the subject and the level of thinking. Topic relevance the use of computer models of various physical processes and phenomena contributes to the effectiveness of teaching physics to students, allowing them to understand the mechanisms of physical phenomena, often invisible to the human eye, and in some cases impractical and impossible in life. In order to identify the advantages of computer modeling, studies were conducted on two groups of 9th grade students (Control and experimental), their general understanding in the use of computer modeling was studied, and the role of computer modeling in understanding the concepts of speed and acceleration in body movement was determined. The two groups were applied the same traditional type of training on this topic, and the peculiarity was that the experimental group used computer simulations as a complement. Based on the results presented in the studies, it is shown that students working with the help of computer modeling scored significantly higher scores in their tasks. After analyzing the results, it is confirmed that computer modeling can be used as an additional teaching tool that helps to increase the level of thinking of students, as well as to develop systemic ideas about phenomena in physics. In the course of research using modeling, on average, 6 out of 10 students achieved good results. The importance of teaching using computer models, organizing the student's interaction with the model to participate in active research activities is revealed. It was also found that computer models can be used both in distance learning and in traditional learning, including with network support. The result of the research is that the training of physics teachers in computer modeling can be used internationally in the training of future physics teachers, enhancing their intellectual abilities, contributing to the performance of mental operations and the development of intelligence in general.
Creating Santripreneurs: Empowerment of Jepara Santri in Entrepreneurship with 3D-Based Furniture Design Training

As technology developed, santri in Jepara started a furniture business with the skills gained when learning in Pesantren (Islamic boarding schools), studying (nyantrik) and training. This training aims to equip students with the skills to design 3D furniture to support their businesses. The training is carried out in two stages: 1) the preparation stage, selecting interested potential participants who have the motivation and potential to set up a furniture business; 2) the implementation stage with lecture, practice, question and answer methods and simulations. The results of the training show that; 1) Santri in Jepara is very interested in the furniture business, so they are excited and could learn 3D furniture design faster; 2) After attending the training, the students are able to: a) operate the SketchUp program and can make simple furniture designs, b) develop furniture designs with various shapes, and some have tried to make carving designs, c) have a great enthusiasm to develop expertise in the furniture business by self-learning through social media.
Detection of The Deaf Signal Language Using The Single Shot Detection (SSD) Method

Sign Language is a language that prioritizes manual communication, body language, and lip movements, instead of sound, to communicate. Deaf people are the main group who use this language, usually by combining hand shape, orientation and movement of the hands, arms, and body, and facial expressions to express their thoughts. Therefore, the researcher created an image recognition program in sign language using the Single Shot Detection (SSD) method, which is a convolution activity by combining several layers of preparation, by utilizing several components that move together and are motivated by a biological sensory system. The letters used in making sign language programs use the letters of the alphabet (az). This sign language detection programming that runs on the Google Collaboratory application
Design of The Population Information System in The Village of Pajajaran

Population or demography is the study of the dynamics of the human population. Demographics includes the size, structure and distribution of a population, and how the population changes over time as a result of births, deaths, migration, and aging. The current population system is still using the manual method, namely using the form provided by the Pajajaran Village, which is deemed less effective and efficient, therefore, there are often miscalculations of the number of residents when reporting to the Cicendo District, Bandung City. This study aims to analyze and design a population system. The design of this population information system uses PHP Native programming and MySQL Database Management System. With the existence of a web-based information system, it is hoped that it will facilitate the making of valid and not fictitious population reports
Archives Effectiveness in Improving Administrative Services

Archiving is very important in an organization, office, or government; archives provide information and a vehicle for documentation. Every employee in an organization, office, or government is required to work effectively and efficiently in supporting organizational goals; so that employees can work effectively, the quality and quantity must be to the organization's needs. This study uses a quantitative research approach. Furthermore, the data that is explored includes primary and secondary data. Data collection techniques through observation, interviews, and documentation. Data has been collected through questionnaires and processed manually with a card system. Based on the results of this processing, the data is tabulated into a frequency table to determine the level of the analyzed variables. The results showed that the effectiveness of archives in improving administrative services in Bulu-Bulu Village, Tonra District, Bone Regency, namely the procedure for creating archives in managing letters was good but had not used a letter sorting tool to sort letters, both incoming and outgoing letters, which made it easier for management to be faster and easier effective. In addition, the Bulu-Bulu Village Office still uses manual archive management but does not use electronics.
Editorial IEEE Transactions on Cognitive and Developmental Systems

In the early spring decorated with pink, white, and yellow plum blossoms, as the Editor-in-Chief of the IEEE Transactions on Cognitive and Developmental Systems (TCDS), I would like to take this opportunity to wish everyone a healthy and productive new year of 2023!
DEVELOPMENT OF A BASED LEARNING MODEL TO IMPROVE STUDENT LEARNING OUTCOMES IN ENGLISH LEARNING IN SUGGESTION/ADVICE MATERIAL IN CLASS XI MIPA 1 SMA NEGERI 1 BANDUNG

This study aims to develop a Problem Based Learning learning model to improve English learning outcomes on suggestion or advice material in class XI MIPA at SMA Negeri 1 Bandung. This study aims to improve students abilities. The method used is the development research method (Research &amp; development). Meanwhile, the development of learning and research will produce a new way or syllabus in teaching learning that will provide motivation to students. The results of research with the application of the PBL learning model can significantly improve student learning outcomes. This is evident from the acquisition of scores before and after the application of the PBL learning model. The results of the average pretest score of 55.50% were in the Less category, which reached the KKM score of 3 people (8.33%). In cycle 1 after implementing the PBL learning model, the average score was 75.02, categorized as Good, which achieved a KKM score of 19 people (52.77%). In the second cycle, the average score increased again to 86.08, in the Very Good category, which reached the KKM score of 34 people (94.44%). KEYWORDS: learning model Problem Based Learning, research and development methods (Research &amp; development and learning English)
Recent Applications of Smartphone and Smart Glasses in Applied Science and Engineering

Today, more than 3 [...]
Analisa Proteksi Gangguan Petir Pada SUTT 70 KV Antara GI Kebonagung - Polehan

In maintaining the continuity of its distribution, routine maintenance and a good security system are needed to anticipate abnormal conditions. This study analyzes lightning disturbances along the 70 kV transmission line from the Kebonagung substation to the Polehan substation with different strike point conditions, as well as studies the condition of the equipment when a direct strike occurs in the 70 kV transmission. From the results of the analysis when a direct strike on the phase wire of 1098 kV goes to the Kebonagung Substation, the arrester will work to throw the overvoltage to the ground, so the lightning voltage that reaches the Kebonagung Substation equipment is less than 60 kV so that the equipment at the Kebonagung Substation is protected from disturbance lightning. However, if the arrester does not work when there is a direct strike, then the damaged equipment is CVT (739.26 kV), Ds Line (545.56 kV) and CT (378.274 kV), because the BIL of the equipment is smaller than the lightning voltage that reaches and causing the system to shut down. When an indirect strike of 97.068 kV goes to the Kebonagung substation, the arrester will work and the equipment at the Kebonagung substation is protected. However, if the arrester does not work, the equipment is still protected because the CVT (65.347 kV), DS Line (16.95 kV) and CT (4.230 kV), the BIL of each equipment is higher than the incoming lightning voltage.
The sigma Accessibility Special Interest Group: Resources Update

This article contains a short update on the work of the sigma Accessibility Special Interest Group. We announce the release of resources to assist mathematics tutors and coordinators with the support of mature students and those with dyslexia, dyscalculia and dyspraxia. We provide a brief background to the development of these resources and describe their pilot in two institutions, one in England and the other in Ireland. We close with a description of the next stages of work for the special interest group and a call for additional people to get involved.
INEOS Styrolution's Styroflex® binder for bio-based products

On February 28, 2023, INESO Styrolution claimed that their Styroflex® SBC[1] product is a superior, cost-effective binder for bio based products such as cork. The new solution is a cork-Styroflex®-compound reportedly requiring no further additives or additional binders. It is expected to be a cost-effective and fully recyclable alternative to commonly used Polyurethane based binders.
Social Media Influencer and Copycat Crisis: Focus on the Trademark Law Infringement

This study aims to explore how consumers react to IPR-related crises by examining the Social Media Influencer (SMI) 's trademark infringement advertisement case with two experimental conditions: (a) intentionally copied advertisement (ICA) and (b) unintentionally copied advertisement (UCA) using attribution theory and expectancy violation theory. For the main study, we recruited 133 female respondents aged in their 20s to 40s who had previously subscribed to SMI advertisements. As a result, the findings showed that consumers do significantly more blame the collaborating brand in the case of UCA. However, consumers also feel their expectancy is more violated when the SMI is unintentionally involved in trademark infringement. If SMIs frame this crisis as having occurred by negligence and ignorance, consumers may have cognitive dissonance between the previous authentic reviews and the ignorance. The findings can contribute to figuring out overall consumer responses to the IPR infringement legal crisis.&nbsp
Service Design: Developing A Creative Ideation and Low-Tech Rapid Prototyping Toolkit for Multicolores Embroidery Project

The Purpose of this design research was to develop a creative ideation and low tech rapid prototyping toolkit based on artisan-defined needs and criteria. The aim was apply creative expertise responsively, toward the beneficial use and in service to others. Cross-cultural design interventions ideally respect and attempt to encourage artisanal creativity and agency.&nbsp; In this scenario, the design researcher bridges a gap, facilitating artisans in an effort to better compete with the products and practices of modern industrialization.
Prospects of Ant Colony Optimization(ACO) in Various Domains

The various prospects of Ant Colony Optimization(ACO) highlighting the versatile nature of the algorithm in a wide range of resource allocation problems in domains is presented. The problem representation in each of the domains is illustrated for a researcher keen on working with ACO. The mechanics of ACO that control and enhance its performance are also explored in each application. The various libraries available for testing discrete and continuous problems in ACO are demonstrated. ACO has some limitations and the prospects of hybrid versions of ACO and the scope for further research are presented and discussed.