Reviewerly/exHarmony huggingface dataset:
Improving the quality of the technological process of packaging shape formation based on the information structure of an automated system

Based on the information structure of an automated quality monitoring system, we have designed a system to analyze information on the quality of forming the shape of PET-packaging, with a possibility of statistical control over the technological process using Shewhart control charts. That has been demonstrated using an example of the proposed technique of quality estimation of the finished PET bottles based on the thickness of their walls. Obtaining high-quality PET-packaging directly depends on the degree of perfection of all technological stages, thereby predetermining the necessity to build an effective system to control and manage the technological process of the shape formation of bottles made from polyethylene terephthalate.An analysis of information about the quality of PET-packaging shape formation based on monitoring the information structure of an automated system would make it possible to ensure operative adjustment of shape forming parameters at the minimized percentage of defects by organizing selective control over the products made. The use of statistical methods based on Shewhart control charts could enable the development of authentic algorithms for monitoring the shape formation quality aimed to track violations of technological parameters and compile recommendations on improving the process quality, as well as resource-use efficiency.The statistical estimation of cause-effect relations between the main technological parameters and product quality indicators involves the algorithm that monitors the quality of PET-packaging shape formation. This makes it possible to ensure the minimum level of defects in bottles when applying the devised Shewhart control chart.We have proposed a fuzzy cognitive chart for defining the preventive corrective actions directed at the elimination of the main causes of a defect at bottle shape formation, taking into consideration the interrelations of factors and their consequences on the resulting process quality
Pemanfaatan Media E-Learning Moodle Untuk Menunjang Pembelajaran Mahasiswa di Fakultas Manajemen dan Bisnis Universitas Ciputra

AbstrakVery rapid technological developments in this current era of globalization provide so many benefits in many social aspects. The use of the technology is used by the humans to facilitate every humans job. The development of technology does not only help humans in the industrial field, but also in education. This is done so that future generations are not left behind and can help to build a nation's progress. The purpose from thid study was to analyze the use of moodle e-learning media to support student learning at the Faculty of Management and Business at Ciputra University. This type of research is a qualitative descriptive study conducted at the Faculty of Management and Business at Ciputra University. Data collection techniques are done by conducting interviews and documentation. While the data analysis techniques go through several steps, namely: data collection, data reduction, data presentation, and drawing conclusions or verification. The results show that: 1) moodle e-learning media is considered interactive because it has features that make interaction between students and lecturers more enjoyable, especially as mentioned earlier that with the help of an application called 'zoom' then activities such as video conferencing can done anywhere, and not only that they can also make presentations or do quizzes, exams, and other activities that are usually done in class; 2) the use of moodle e-learning media is indeed very easy, mainly used as a learning medium as a helper or substitute for learning activities in class, in the sense that activities in the classroom can still be done even if the lecturer or student are not in the same area, but still, the lecturer able to provide material and students can also continue to receive material from lecturers even though they are outside the classroom.
Socioeconomic and clinical-epidemiological profile of people attended in an outpatient clinic for complex wounds

Objective: to characterize the socioeconomic and clinical-epidemiological profile of people attended in an outpatient clinic specialized in complex wounds. Methods: cross-sectional study with 69 people with wounds, through the application of a questionnaire. Data analyzed using descriptive and analytical statistics. Results: most participants were male (55.1%), above 60 years old (55.1%), married (40.6%), income from one to three minimum wages (69.6%). Regarding clinical aspects, 50 (72.4%) had the injury for more than six months, 32 (46.4%) had a relative responsible wound dressing, 44 (63.8%) did not have difficulties in wound dressing. Regarding how long they had the wound, pain and arterial disease were statistically significant (p=0.042; p=0.026). Conclusion: most participants were male and above 60 years old. Pain and the presence of arterial diseases were significant with regards to people with chronic wounds.
Unsupervised Hybrid Algorithm to Detect Anomalies for Predicting Terrorists Attacks

This work presents a hybrid approach for unsupervised algorithms (UHA), in order to extract information and patterns from data concerning terrorist attacks.The reference data are those of the Global Terrorism Database.The work presents an approach based on autoencoders and k-modes type clustering.The results obtained are examined through some metrics presented in the article and it is also considered methodologically how to determine a robust threshold for anomaly detection problems.
A Perceptually Coherent TMO for Visualization of 360$$^\circ $$ HDR Images on HMD

We propose a new Tone Mapping Operator dedicated to the visualization of 360 $$^\circ $$ High Dynamic Range images on Head-Mounted Displays. Previous work around this topic has shown that the existing Tone Mapping Operators for classic 2D images are not adapted to 360 $$^\circ $$ High Dynamic Range images. Consequently, several dedicated operators have been proposed. Instead of operating on the entire 360 $$^\circ $$ image, they only consider the part of the image currently viewed by the user. Tone mapping a part of the 360 $$^\circ $$ image is less challenging as it does not preserve globally the dynamic range of the luminance of the scene. To cope with this problem, we propose a novel Tone Mapping Operator which takes advantage of 1) a view-dependant tone mapping that enhances the contrast, and 2) a Tone Mapping Operator applied to the entire 360 $$^\circ $$ image that preserves the global coherency. Furthermore, the proposed Tone Mapping Operator is adapted to the human eye perception of the luminance on Head-Mounted Displays. We present two subjective studies to model the lightness perception on such Head-Mounted Displays.
Estimation of the Range of Variation in the Mineral Composition of Silicate Lake Bottom Sediments Using Data from XRD and XRF

A method is proposed for estimating the range of mineral group content in the cores of silicate bottom sediments of lakes based on the search for the minimum and maximum content of stoichiometric minals that make up the group of minerals, provided that the balance of the mineral composition and the content of elements in the sample is observed. The mineral components were determined using the method of qualitative X-ray phase analysis, the contents of the main rock-forming elements were determined by X-ray fluorescence analysis. Comparison with the results of quantitative X-ray phase analysis showed that the contents of mineral groups either lie in the range calculated in the extreme search procedure based on data on the element composition, or overlap with the calculated range within the measurement error. The systematic discrepancy between the results of calculating the range of content of the silicon dioxide phase and the results of quantitative X-ray phase determination of quartz observed for the samples under consideration is due to the presence of an X-ray amorphous phase of biogenic silica. The proposed method for estimating the range of mineral group content is easy to implement, uses the publicly available MS Excel software, and can be useful for estimating variations in mineral composition by core depth, in conditions of frequent shortages of individual sample material distributed between different methods of analysis
Penerapan Logical Unit Number (LUN) Pada Drobo Virtual Storage Dengan Metode Network Development Life Cycle (NDLC)

In line with the development of a company that is increasingly large as the development of information technology is used, which in turn will also affect the provision of storage devices that can display data that operate for 24 hours.This is what drives PT.Pertiwi Agung, which will currently develop its business, even though it currently has a market share around Southeast Asia.The company must be able to store all the data which can certainly be very large.For this reason, a media is needed, the media is Virtual Storage which is managed by Drobo, an external storage device that relies on a Logical Unit Number that can identify all equipment used.To be more targeted, the process of implementing the Logical Unit Number in Virtual Storage uses the Network Development Life Cycle (NDLC) method.The result of applying the Logical Unit Number is that this considerable amount of data can be read and integrated, even though the storage media is spread in several places.
Authentication and Key Management Automation in Decentralized Secure Email and Messaging via Low-entropy Secrets

We revisit the problem of entity authentication in decentralized end-to-end encrypted email and secure messaging to propose a practical and self-sustaining cryptographic solution based on password-authenticated key exchange (PAKE). This not only allows users to authenticate each other via shared low-entropy secrets, e.g., memorable words, without a public key infrastructure or a trusted third party, but it also paves the way for automation and a series of cryptographic enhancements; improves security by minimizing the impact of human error and potentially improves usability. First, we study a few vulnerabilities in voice-based out-of-band authentication, in particular a combinatorial attack against lazy users, which we analyze in the context of a secure email solution. Next, we propose solving the problem of secure equality test using PAKE to achieve entity authentication and to establish a shared high-entropy secret key. Our solution lends itself to offline settings, compatible with the inherently asynchronous nature of email and modern messaging systems. The suggested approach enables enhancements in key management such as automated key renewal and future key pair authentications, multi-device synchronization, secure secret storage and retrieval, and the possibility of post-quantum security as well as facilitating forward secrecy and deniability in a primarily symmetric-key setting. We also discuss the use of auditable PAKEs for mitigating a class of online guess and abort attacks in authentication protocols.
A Multiparty Chat-Based Dialogue System with Concurrent Conversation Tracking and Memory

Most of the recent developments in conversational agents only consider interactions with one user at a time. To interact with multiple users at the same time, extensions to the two-party dialogue system framework have been explored. However, this approach either assumes that multiparty interactions can be approximated by a sequence of two-party independent conversations, or compromises the agent's capacity for individual engagement (i.e., recalling user preferences and details from previous interactions). In this work, these limitations are addressed through two novel contributions. First, we develop a module that keeps a concurrent record of conversations, where each conversation is explicitly marked as a group or individual discussion. Second, we extend the intent framework to include agent memory across multiple timescales. This allows conversational agents to reason about past interactions by recalling previously recorded intents. The practical application of the system is verified using a case study on a real-world chat-based conversational agent implementation.
SAPTM: Towards High-Throughput Per-Flow Traffic Measurement with a Systolic Array-Like Architecture on FPGA

Per-flow traffic measurement has emerged as a critical but challenging task in data centers in recent years in the face of massive network traffic. Many approximate methods have been proposed to resolve the existing resource-accuracy trade-off in per-flow traffic measurement, one of which is the sketch-based method. However, sketches are affected by their high computational cost and low throughput; moreover, their measurement accuracy is hard to guarantee under the conditions of changing network bandwidth or flow size distribution. Recently, FPGAplatforms have been widely deployed in data centers, as they demonstrate a good fit for high-speed network processing. In this work, we aim to address the problem of per-flow traffic measurement from a hardware architecture perspective. We thus design SAPTM, a pipelined systolic array-like architecture for high-throughput per-flow traffic measurement on FPGA. We adopt memory-friendly D-left hashing in the design of SAPTM, which guarantees high space utilization during flow insertion and eviction, successfully addressing the challenge of tracking a high-speed data stream under limited memory resources on FPGA. Evaluations on the Xilinx VCU118 platform with real-world benchmarks demonstrate that SAPTM possesses high space utilization. Comparisons with state-of-the-art sketch-based solutions show that SAPTM outperforms comparison methods in terms of throughput by a factor of 14.1x–70.5x without any accuracy loss.
STUDENTS’ AND TEACHERS’ PERCEPTIONS OF USING ELECTRONIC TEXTBOOKS IN EDUCATIONAL PROCESS

The research evaluates the effectiveness of using electronic textbooks in educational process compared to printed publications. The advantages and disadvantages of introducing e-textbooks in higher education institutions are determined. The problems that students face while working with e-textbooks are outlined. Based on the literature analysis, the authors claim that e-textbooks are more convenient and are being increasingly used in the educational process. A standardised questionnaire including 17 questions was developed by authors to determine students' and teachers' perceptions of using e- textbooks in educational process. Data analysis tools comprise the methods of mathematical and descriptive statistics. According to the survey, users want to get cheap but high-quality e-textbooks, with a high level of production, without errors, and with completeness of information. The price and the quality play a crucial role in decision making. Also, the criterion of e-textbooks friendliness is of great importance, including ease of search, the ability to navigate by hyperlinks, and adaptive layout for different devices. The problem of standardisation of e-textbooks may be the subject of further research and practical development.
A new approach to generate diversified clusters for small data sets

Clustering is a common data mining technique whose main principle states that the samples within a cluster are similar to one another and dissimilar to those in other clusters. This means that samples in the same cluster possess high homogeneity, while different clusters possess high heterogeneity. However, a user may require a result of diversified clustering. Compared to traditional clustering methods, the aim of diversified clustering is to make samples of the same cluster possess high heterogeneity, and different clusters possess high homogeneity. Diversified clustering can be practically applied to aspects of our daily lives such as normal class grouping, student grouping in learning, cluster sampling, balanced diets and assignment of jobs. Nevertheless, our survey of related papers in the research field of data mining found that there has been no proposed research for diversified clustering. In this paper, we formal define the problem of diversified clustering and propose a new method to solve this problem. Experimental results showed that our method can generate good diversified clustering. However, our method is currently only appropriate for small data sets since the execution time of our method increases quickly as the number of diversified clusters increases. We also hope this paper will garner interest in more research on effective methods to generate diversified clusters for use in data mining.
Angelic Checking within Static Driver Verifier: Towards high-precision defects without (modeling) cost

Microsoft's Static Driver Verifier (SDV) pioneered the use of software model checking for ensuring that device drivers correctly use operating system (OS) APIs. However, the verification methodology has been difficult to extend in order to support either (a) new classes of drivers for which SDV does not already have a harness and stubs, or (b) memory-corruption properties. Any attempt to apply SDV out-of-the-box results in either false alarms due to the lack of environment modeling, or scalability issues when finding deeply nested bugs in the presence of a very large number of memory accesses. In this paper, we describe our experience designing and shipping a new class of checks known as angelic checks through SDV with the aid of angelic verification (AV) [1] technology, over a period of 4 years. AV pairs a precise inter-procedural assertion checker with automatic inference of likely specifications for the environment. AV helps compensate for the lack of environment modeling and regains scalability by making it possible to find deeply nested bugs, even for complex memory-corruption properties. These new rules have together found over a hundred confirmed defects during internal deployment at Microsoft, including several previously unknown high-impact potential security vulnerabilities. AV considerably increases the reach of SDV, both in terms of drivers as well as rules that it can support effectively.
The Use of Multimedia Technology in Early Childhood Literacy

UNESCO shows that the reading interest of Indonesians is in ranks 60 out of 61 countries in the world which shows that the interest of Indonesians in reading and writing is relatively low, therefore, the habit of reading should be introduced to children, by using multimedia technology.This study aimed to describe the use of multimedia technology for literacy learning in early childhood education, including: implementation of multimedia technology utilization in children's literacy learning.This study is a qualitative research.Data collection used observation techniques, interviews and document review.The data validity was obtained through triangulation.The data analysis technique was done using interactive model.The results show that: Implementation of use of multimedia technology in literacy learning was implemented in each step of learning centers with steps:(a) focusing attention, (b) orientation, (c) modeling, (d) child play stage, and (e) summary.
Research and Exploration of Online to Offline (O2O) Blended Teaching for Talent Cultivating

Since ministry of education has targeted "Golden Courses" as one key construction project, a new round of reform for teaching model is looming.Due to unique advantages of the online to offline blended teaching model, it is increasingly being used to practice.This paper comparatively analyzes characteristic of current class and superiority of online to offline (O2O) blended teaching model.Based on active learning and higer-order teaching goal, application of the online to offline blended teaching for talent cultivating is deeply explored.Moreover, an improved design of O2O blended teaching, which can be used for reference is proposed.
A Survey on Cyber Security Threats and their Solutions

Cyber attacks have increased nowadays in a rate which cannot be tackled through minimum security policies which we have for protecting our information inside the computer like creating passwords, PINs, installing anti-viruses to stop viruses and other threats that troubles our computer system or Firewalls for securing our information inside the network. With the rapid advancements in technology, hackers and other cyber criminals have opted to new modes through which they can steal important user information.To deal with such threats prone to our devices, we have made a survey on different types of cyber security attacks which are more common in today's scenario, their types and mode of attack and precautions that we can take to tackle such threats.We will study the tactics and measures adopted so far to tackle the problems created by these threats and make a comparative account on the different types of threats that are mostly effective in modern day context and their increase or decrease in the rate of prevalence per year.
The Impact of Innovation Strategy on Organizational Success: A Study of Samsung

The purpose of this study is to examine the impact of Samsung’s innovative strategy on organizational success. Today, the smartphone market has been fast evolving and it becomes a necessity to mankind. Samsung, one of the giant players which dominates the global smartphone market, has carried out innovative strategies, such as releasing smartphones with new features that cater the needs of customers, and achieves higher sales compared to its competitors in the smartphone market. This study emphasizes the innovative strategies that lead to Samsung's success. Besides, this study also looks at Samsung's opportunity and creativity to gain smartphones innovative leadership based on the 5G emerging technology. The finding of this study indicates that innovative strategy is positively related to the success of the organization.
Anomaly Detection with Discrete Minimax Classifier for Imbalanced Dataset or Uncertain Class Proportions

Supervised classification is becoming a useful tool in condition monitoring. For example, from a set of measured features (temperature, vibration, etc.), we might be interested in predicting machine failures. Given some costs of class misclassifications and a set of labeled learning samples, this task aims to fit a decision rule by minimizing the empirical risk of misclassifications. However, learning a classifier when the class proportions of the training set are uncertain, and might differ from the unknown state of nature, may increase the misclassification risk when classifying some test samples. This drawback can also occur when dealing with imbalanced datasets, which is common in condition monitoring. To make a decision rule robust with respect to the class proportions, a solution is to learn a decision rule which minimizes the maximum class-conditional risk. Such a decision rule is called a minimax classifier. This paper studies the minimax classifier for classifying discrete or discretized features between several classes. Our algorithm is applied to a real condition monitoring database.