Reviewerly/exHarmony huggingface dataset:
IMPLEMENTASI APLIKASI STOCK OPNAME BERBASIS WEBSITE APP PADA PERUBAHAN PROSES BISNIS DI PT WELL CHOIS APPAREL

Abstract:The implementation of the website-based stock taking application on business changes at PT Well Chois Apparel is the implementation of the stock taking application provides a solution to increase convenience and speed for PT Well Chois Apparel in finding data that can be said to be valid between the amount of stock in the warehouse compared with the data recorded in workbook that have been entered into a web-based database system; then the most important thing is the ease in carrying out the process of reporting inventory item to the Director of PT Well Chois Apparel; the inventory of goods carried out produces reports with data that can be said to be accurate and very quickly obtained; the other thing is the ease of access for company director to find out the current stock of goods by using a web-based application, every time the director needs it; and the last is this application can reduce errors that occur in recording manually due to obscurity from the writing that is written on the workbook.
How Blockchain Technology Can Benefit Marketing: Six Pending Research Areas

The proliferation of sophisticated e-commerce platforms coupled with mobile applications has ignited growth in business-to-consumer (B2C) commerce, reshaped organizational structures, and revamped value creation processes. Simultaneously, new technologies have altered the dynamics of brand marketing, enabling a broader reach and more personalized targeting aimed at increasing brand trust and enhancing customer loyalty. Today, the Internet allows marketers to penetrate deeper into their existing markets, create new online marketplaces and to generate new demand. This dynamic market engagement uses new technologies to target consumers more effectively. In this conceptual paper, we discuss how blockchain technology can potentially impact a firm's marketing activities. More specifically, we illustrate how blockchain technology acts as incremental innovation, empowering the consumer-centric paradigm. Moreover, blockchain technology fosters disintermediation, aids in combatting click fraud, reinforces trust and transparency, enables enhanced privacy protection, empowers security, and enables creative loyalty programs. We present six propositions that will guide future blockchain-related research in the area of marketing.
A Neural Network-based Multisensor Data Fusion Approach for Enabling Situational Awareness of Vehicles

With the growing number of research studies on Vehicle-to-Vehicle (V2V) communication applications, situational awareness becomes one of major challenges for autonomous vehicles. Autonomous vehicle needs to predict the movement and trajectories of surrounding vehicles accurately in order to make a better decision making. The ability to recognize vehicles' surroundings has become important in order to enable situational awareness and navigate the vehicle safely. In this paper, we propose a neural network called Mapping Decision Feedback Neural Network (MDFNN) to tackle the vehicle identification (VID) issue in V2V communication. According to the MDFNN infrastructure, two types of MDFNN namely as Grid-based MDFNN and Bounding box-based MDFNN are proposed. The MDFNN fuses image, V2V interface, GPS, magnetometer, and speedometer data (i.e., multi-sensor data and V2V communication) to enable situational awareness. MDFNN utilizes the mapping decision feedback information in the proposed deep learning neural network structure. With this improvement, a greatly improved accuracy can help to resolve the VID issue. Our experiment's result shows 85% of accuracy for Grid-based MDFNN.
Random Forest for video Text Amazigh

In this paper; we introduce a system of automatic recognition of Video Text Amazigh based on the Random Forest. After doing some pretreatments on the video and picture, the text is segmented into lines and then into characters. In the stage of characteristics extraction, we are representing the input data into the vector of primitives. These characteristics are linked to pixels’ densities and they are extracted on binary pictures. In the classification stage, we examine four classification methods with two different classifiers types namely the convolutional neural network (CNN) and the Random Forest method. We carried out the experiments with a database containing 3300 samples collected from different writers. The experimental results show that our proposed OCR system is very efficient and provides good recognition accuracy rate of handwriting characters images acquired via Video camera phone.
Adoption of IoT technology to estimate evapotranspiration from satellite imagery

Evapotranspiration is one of the most important components of energy and water balance. The most important way to get real large-scale evapotranspiration is to utilize satellite imagery and remote sensing. Implementation of evapotranspiration calculation algorithms such as SEBAL demands calculation of reference evapotranspiration and thus measuring air temperature, humidity and wind speed. Calculation of evapotranspiration is usually based on obtained information from the nearest weather stations to the study area, which can be error-prone. Therefore, in this study, IoT sensors were used to accurately measure air temperature at 2 m above the ground, as well as air humidity and wind speed in the study area. The study area is the farms of Moghan Agricultural Company in Ardabil province. In this study, 23 nodes were installed in a number of farms. The ground-based energy balance algorithm (SEBAL) was used to calculate the evapotranspiration using Landsat 8 images in 2015.
Automatic Determining Of Candidate Keys Sets Depending On Functional Dependency

This paper presents a step in automatic database design, re-engineering and schema modification, design weak points detection, and normalization. This step represents determining the candidate keys of the tables automatically via proposing and implementing an algorithm which depends on the functional dependency and attribute set closure. Also, some techniques of Apriori algorithm of association rule mining are used to generate keys and minimize the keys space. The implementation is done by using Oracle PL/SQL to utilize the facilities provided by ORACLE DBMS and to give the features of embedded system to the proposed one.
Enhanced Fuzzy Rule Based Contrast Limited Adaptive Histogram Equalization

In recent years, tremendous research is being conducted in the field of computer technology. Our technical standards are improving day by day. Image preprocessing plays an important role in many fields of study that use computer technology. Pre-processing techniques are used to detect diseases in medical imaging. . In computer vision, images obtained with digital cameras are usually damaged by decoding errors or positive and negative pulses generated in noisy channels. When an image is digitized, it can be manipulated through a variety of image processing tasks. In image processing, noise removal is important for improving image quality, which is done by a technique called filtering. Filtering techniques and their algorithms play an important role in calculating and comparing peak signal-to-noise ratio (PSNR) values to eliminate noise and estimate noise. Image filters have three domains: spatial domain, frequency domain and fuzzy domain. Sometimes other filtering techniques appear, but when the experimental results appear, false alarm rates sometimes appear, but now removing noise from the original image is still a problem for researchers. The purpose of this white paper is to enhance the image based on fuzzy powerful preprocessing techniques and related latest work. Finally, analyze the experimental results through performance evaluation.
RANCANG BANGUN MEDIA PEMBELAJARAN PENGENALAN PERANGKAT LUNAK UNTUK SISWA SEKOLAH DASAR

The introduction of computers in elementary schools is deemed necessary because, along with technological advances in the present, children must begin to be introduced to terms in computers. Software or what is often called software is one part of the computer. Learning media is a way for children in elementary schools to learn about software. Learning media has a very important role in education and training activities. Learning media that are used can help facilitate learning effectively and efficiently. The purpose of this research is to design a software learning media for elementary school children as a basic introduction to the software itself. In this study using Macromedia Flash 8 software and using the Research and Development (R&D) method, while the development model uses ADDIE . Key words : software, media, learning.
Digital educational environment as a system-forming element of digital didactics

Digitization in education is one of the most actual issues in modern society. COVID-19 pandemic and connected with it lockdown showed the necessity of an urgent transition of educational processes of different levels to a mixed or distant education. Such changes in paradigm do not suggest the digitalization of the traditional content, but the creation of an educational system based on digital didactic principles. The article deals with the problem of designing, creation and testing of digital educational environment. The analysis of the researches enables to define the notion ‘digital educational environment’ and identify its components. The conducted questionnaire of 132 university and college teachers in Ukraine, who provided distant education during COVID-19 lockdown, demonstrated a positive qualitative increase of motivation criterion for the formation and application of all the components of digital educational environment, and allowed to identify the main problems, tackling of which is possible due to synergy of the state, science and system of education.
Experiential Learning as Learner Centered Approach (LCA) in English Language Classroom

English language has been enjoying a privileged status in India and occupies a vital place not only in the lives of people but also in Education.English stretches out and expands in all walks of life, from consumer packing to popular magazines, and has a great influence on economic development.Despite the importance of English, the reality of this language in India has not reached the heights of international standards.Efforts to make learners more competent in English language communication are a reality yet to be achieved as revealed in several studies.The current study proposes experience, which is a basis of fundamental and natural learning available to everyone that can be utilized towards the learning of the language by students.In addition, the language teachers are invited to recognize the in-built capacity of the experience in students to foster their learning process.This article, an exploratory study through a quantitative method was carried out among a group of students, in several schools, in the city of Chennai.The results revealed the significance and the utility of Experiential learning, as one such engaging method based on Learner Centered Approach to the learning of English as a second language
Multi-timescale Representation Learning in LSTM Language Models

Language models must capture statistical dependencies between words at timescales ranging from very short to very long. Earlier work has demonstrated that dependencies in natural language tend to decay with distance between words according to a power law. However, it is unclear how this knowledge can be used for analyzing or designing neural network language models. In this work, we derived a theory for how the memory gating mechanism in long short-term memory (LSTM) language models can capture power law decay. We found that unit timescales within an LSTM, which are determined by the forget gate bias, should follow an Inverse Gamma distribution. Experiments then showed that LSTM language models trained on natural English text learn to approximate this theoretical distribution. Further, we found that explicitly imposing the theoretical distribution upon the model during training yielded better language model perplexity overall, with particular improvements for predicting low-frequency (rare) words. Moreover, the explicit multi-timescale model selectively routes information about different types of words through units with different timescales, potentially improving model interpretability. These results demonstrate the importance of careful, theoretically-motivated analysis of memory and timescale in language models.
Achieving cybersecurity improvements through Enterprise Systems Engineering

The Critical Infrastructures (CI) that provide essential services such as energy, water and transport have been undergoing a digital transformation to achieve more effective and efficient operations. These changes are increasing the potential attack surface and exposure to cybersecurity incidents. The EU Directive on Security of Network and Information Systems (NIS Directive) (National Cyber Security Centre, 2018) has brought a new emphasis on improving the cybersecurity of essential services. It has introduced mandatory incident reporting and a framework to raise the cybersecurity and resilience levels of CI.Rather than a dislocated approach to managing the system in parts, taking on responsibility for cybersecurity requires an integrated, whole-system governance approach, to discover the full end-toend picture and risk assess the potential gaps in security. The NIS Directive expects cybersecurity to be managed through the wider system of contractors and sub-contractors and vendors to the sector, all participating in a complex adaptive system. From whole organisations down to products, components and data flows, deciding the scope of critical systems that support essential services has integrated activity across different work areas such as operational technologies, enterprise IT and telecoms networks. Understanding the end-to-end system and whole enterprise interactions is necessary to achieve the outcome-based nature of the NIS Directive.This paper investigates the activities that have evolved to secure the broader and deeper supply chains as well as internal networks and systems of CI organisations. Enterprise Systems Engineering (ESE) is introduced as a tool to facilitate the shared cybersecurity requirements across organisations for securing essential services, streamlining whole system security behaviours of people, processes and technology towards a more resilient CI.
RANCANG BANGUN APLIKASI ARSIP AKTA KEPENDUDUKAN BERBASIS WEB PADA DINAS KEPENDUDUKAN DAN CATATAN SIPIL KOTA PONTIANAK

The information technology accelerates so fast. The computer is a device that was created to facilitate human work and help achieving good progress in the manufacture of hardware and software. Dinas Kependudukan dan Catatan Sipil Kota Pontianak does need an existence of an information system that supports and provides satisfactory service for society. For that reason the writer tries to make the final task about The Web-Based Application of Population’s Archives Management in Dinas Kependudukan dan Catatan Sipil Kota Pontianak, which until now has not been computerized. At this time Dinas Kependudukan dan Catatan Sipil Kota Pontianak is a service in charge of serving the community in terms of stewardship of letters that are private or state documents. The existing system in Dinas Kependudukan dan Catatan Sipil Kota Pontianak is still done manually, starting from keeping, arranging and searching the archives, it is possible for the workers to search archives using the numbers in every storage rack and it will spend a lot of time and energy especially when the archives are needed quickly. The Web-Based Application of Population’s Archives Management is the best solution to solve these kind of problems - the problems that exist in this company will be solved by using a computerized system, this company will also gain an effective and efficient activities. By any means this computerized system will help the run of this company in the future. The computerized system is better than the manual system to run more effectively and efficiently and now managing population’s archives will be more conducive than ever before.
Unitary Kernel Quadrature for Training Parameter Distributions

An infinitely wide model is a weighted integration $\int \varphi(x,v) d \mu(v)$ of feature maps. This model excels at handling an infinite number of features, and thus it has been adopted to the theoretical study of deep learning. Kernel quadrature is a kernel-based numerical integration scheme developed for fast approximation of expectations $\int f(x) d p(x)$. In this study, regarding the weight $\mu$ as a signed (or complex/vector-valued) distribution of parameters, we develop the general kernel quadrature (GKQ) for parameter distributions. The proposed method can achieve a fast approximation rate $O(e^{-p})$ with parameter number $p$, which is faster than the traditional Barron's rate, and a fast estimation rate $\widetilde{O}(1/n)$ with sample size $n$. As a result, we have obtained a new norm-based complexity measure for infinitely wide models. Since the GKQ implicitly conducts the empirical risk minimization, we can understand that the complexity measure also reflects the generalization performance in the gradient learning setup.
LibGuides: CHSS Library: Program Guide

The guide provides user information about library hours and location, services and general links
Digital Platforms and Applications for “Online and Offline Copyrighting” Discipline in On-Line Education Format

The article continues our analysis of “Online and offline copyrighting” discipline transformation from traditional offline education format to E-Learning in Saint-Petersburg Electrotechnical university “LETI”. The 2019 polling discovered that students lack offline communication with the lecturer, thus it was decided to introduce a mixed format in 2020. Due to COVID-19 outbreak all the lecturers and students had to change the mixed format to a distant one. The focus is made on the comparative study of students expectations and feedbacks after the introduction of E-Learning (by using different digital platforms and applications - open.etu.ru, Zoom, Discord, Big Blue Button, Skype) and offline education format. The research embraced 105 students and 5 lecturers.
Klasifikasi Rendaku Dalam Buku Basic Kanji Volume I dan Volume II

The title of this research is Rendaku Classification in Basic Kanji Books Volume I and Volume II. Rendaku is the change of the non-voice consonants into a voiced consonant. The purpose of this research is to classifying the consonant changes of rendaku in Japanese language. This research is a qualitative descriptive study with data collection technique using the literature study tecniques. The method of analysis in this research is the determinants element technique. There are 38 data in the form of wago containing rendaku changes. Data source taken from Basic Kanji Volume 1 and Volume 2. The results of the analysis in this research found the changes in k→g as many as 10 data, changes in h→b as many as 7 data, changes in s/ts→z as many as 4 data, changes in t→d as many as 4 data. Based on the results of the analysis can be conclude that: 1) rendaku will appears on compound words, 2) rendaku will appear if in the second morpheme there are no other voiced consonant. Rendaku happened to morphemes kawa, kami, kata, kaki, ki, kaeri, kuchi, kuni, kusuri, kuruma, ha, hatake, harai, hiki, hito, hi, hosoi, sakana, sama, tsukuri, tsuyoi, tome, toshi, tomo, tera.
Pedagogical morality as a basis for the formation of the moral personality

Pedagogical morality as a basis for the formation of the moral personality
REFLECTING THE PROBLEM OF DESTRUCTIVE SOCIALIZATION OF PERSONALITY IN THE INTERNET ENVIRONMENT

The article examines the destructive socialization of the individual from the point of view of the synthesis of philosophical and pedagogical approaches. The first considers it as a phenomenon that arises in the programs of propaganda of destructive cults, implemented through the use of modern information and communication technologies; the second approach is aimed at finding possible ways to solve the indicated problem, which is investigated within the framework of media pedagogical science, which closely correlates with the processes of interaction between the subject of information and its media agent. The work focuses on the formation of a new vector in the development of media pedagogy by rethinking its target content.
El discurso tecnológico desde la preparación académica de los docentes universitarios mediada por las tecnologías informáticas

The insertion of technologies in the educational process requires a teacher who is better prepared academically and who is equipped with the professional skills that allow him/her to use the didactic resources that are in the university network supported by the academic portal. University teachers must offer the Learning and Knowledge Technologies (LKT) as a reorientation of the Information and Communication Technologies not only in the use of these services as a support tool for teaching, its implementation and use must involve the work of the teacher-student so that the work with the educational resources, enrich the knowledge and procedures during the teaching-learning process in a more dynamic and profound way. The adequate use of the TACs, educational software, virtual learning environments, together with other technological resources found in the university network, impose new ways of exploiting them in initial training. Access to and use of these contemporary didactic means in a coherent manner in the cognitive and pedagogical processes enhances the use of technological discourse in university teachers.
A Neural Network Application of Fully Homomorphic Encryption for Cloud Computing

Cloud computing is a very convenient way of processing huge databases while sharing resources. Currently there are many cloud services available at comparatively low costs, which encourages researchers in the ﬁeld of Machine and Deep Learning to use them. The problem with clouds is their inherent insecure nature. Hence sensitive sectors like health care and banking, are hesitant to use these services. In this paper we provide a proof of concept for applying “Fully Homomorphic Encryption” to process images on clouds for Neural Network application. We demonstrate the success of FHE on black-and-white, grayscale and color images, Gaussian ﬁltering and on Convolutional Neural Network (CNN) for image classiﬁcation, to some extent.
Mose: A Mobile Application for Women Street Vendors in Cape Town

Information and communication technologies make waves in developed and developing countries. However, lack of community involvement in the design and implementation often contributes to failure of technology projects. Our project envisioned a mobile application to enable women to form ad hoc cooperatives to sell on behalf of one another; enabling non-selling women to focus on other tasks. Through the lenses of the Sustainable Livelihoods Framework and the Technology Acceptance Model, we engaged with women vendors to learn of their lived experiences. Results showed they were hesitant to form groups with other women due to a lack of trust. The interaction and feedback from participants yielded incremental co-design and development of several iterations of a mobile prototype; resulting in a final modification to allow for standalone users, whilst also accommodating groups; with groups benefiting by lowering travelling costs by allowing group members to rotate days going to the market when trust materialises.
Upgrading App Volumes

The App Volumes solution is evolving all the time, with new versions and new features. To take advantage of these new features, plus any bug fixes and patches, and to remain on a supported platform, you may need to update your existing deployment.