Client Requests Research Articles

Microblading Technique for Tattooing of "Hairstrokes" That Simulate Natural Hair: Eyebrow Tattooing and Correction of Medical Conditions.

Microblading is a rapidly expanding technique in cosmetic and medical tattooing, used for eyebrow correction and conditions of hair loss. Tattooing is performed by hand using a special blade; tiny cuts in the outer skin are filled with dark pigment to simulate a natural hair. Indications, the technique, and the microblading procedure step-by-step are considered in what follows. Details on client selection and a range of pitfalls are discussed. The leading application of microblading is cosmetic tattooing of the eyebrows adding pigmented "hairstrokes" to the natural brow area. Tattooed "hairstrokes" fade in color over months and a repeated "touch up" procedure may be required. Pretreatment with laser removal of tattoos of the past may be indicated when a client requests a "touch up" with another brow in another style, shape, or extension. Microblading carries the risk of scarring. The combination with conventional machine-driven needle tattooing for background shading the skin of the brow is also discussed. Microblading is also used as a corrective intervention in a range of dermatological and medical conditions. Having grown exponentially for cosmetic purpose in the first phase of microblading parallel to acquired refinement, the method is now mature and ready to make further progress on medical indication in the coming second phase. The medical community should welcome this opportunity for supplementary correction with restoration of the normal brow anatomy added to other achievements in dermatological and medical therapy.

Data Lake Architecture for Storing and Transforming Web Server Access Log Files

Web server access log files are text files containing important data about server activities, client requests addressed to a server, server responses, etc. Large-scale analysis of these data can contribute to various improvements in different areas of interest. The main problem lies in storing these files in their raw form, over long time, to allow analysis processes to be run at any time enabling information to be extracted as foundation for high quality decisions. Our research focuses on offering an economical, secure, and high-performance solution for the storage of large amount of raw log files. Proposed system implements a Data Lake (DL) architecture in cloud using Azure Data Lake Storage Gen2 (ADLS Gen2) for extract–load–transform (ELT) pipelines. This architecture allows large volumes of data to be stored in their raw form. Afterwards they can be subjected to transformation and advanced analysis processes without the need of a structured writing scheme. The main contribution of this paper is to provide a solution that is affordable and more accessible to perform web server access log data ingestion, storage and transformation over the newest technology, Data Lake. As derivative contribution, we proposed the use of Azure Blob Trigger Function to implement the algorithm of transforming log files into parquet files leading to 90% reduction in storage space compared to their original size. That means much lower storage costs than if they had been stored as log files. A hierarchical data storage model has also been proposed for shared access to data over different layers in the DL architecture, on top of which Data Lifecycle Management (DLM) rules have been proposed for storage cost efficiency. We proposed ingesting log files into a Data Lake deployed in cloud due to ease of deployment and low storage costs. The aim is to maintain this data in the long term, to be used in future advanced analytics processes by cross-referencing with other organizational or external data. That could bring important benefits. While the proposed solution is explicitly based on ADLS Gen2, it represents an important benchmark in approaching a cloud DL solution offered by any other vendor.

УДОСКОНАЛЕННЯ МЕТОДУ ПРИЗНАЧЕННЯ ЗАДАЧ ДЛЯ СПІВРОБІТНИКІВ СТАНЦІЇ ТЕХНІЧНОГО ОБСЛУГОВУВАННЯ ТРАНСПОРТНИХ ЗАСОБІВ НА БАЗІ ГЕНЕТИЧНОГО ТА УГОРСЬКОГО АЛГОРИТМІВ

The method of automated process of assigning tasks to employees of vehicle service stations based on genetic and Hungarian algorithms has been improved, which, unlike existing ones, takes into account the complexity of the task, the time of task execution and the qualifications of workers, and also allows to speed up and optimize the workflow at vehicle service stations. To evaluate the optimality of solution options, a new criterion is proposed, which, in addition to the qualifications of the worker, the complexity and time of the task, allows taking into account the needs of the enterprise in different seasons. The experimental data of the proposed algorithms were computerized. The initial data for the computer experiment were taken as data on the functioning of a real service station in Vinnytsia with and without the automated application of an improved method of assigning tasks to employees of a vehicle service station based on genetic and Hungarian algorithms. Computer experiments have shown that genetic algorithm work better with a large number of tasks, and the Hungarian algorithm works better with a small number of tasks. On the basis of the proposed improvements and algorithms, a cross-platform automated system for vehicle service station employees has been developed, which, unlike existing ones, provides instant interaction between the system's software modules, thanks to the microservice architecture and takes into account the high load of client requests, due to the horizontal scaling of the servers that host the system software. A special feature of the automated system is that it provides station employees with an automated workplace where they can manage their own tasks and monitor and control their execution, which allows vehicle service station owners to control the entire customer service process and correctly prioritize tasks for their employees.

Analysis of selected features of application based on monolithic and microservice architecture

The article describes the performance of applications built in monolithic and microservice architectures. The base of research includes application supporting prescription management developed with the use of Spring Framework technology and implemented in the Docker Swarm test environment. The tested applications were subjected to various loads in the form of sending HTTP requests that simulated user behaviour. The research has proven that an application created based on microservices architecture offers better traffic handling in case of high load. Scaling a microservice application allows for greater gains in performance measured as quantity served client requests per unit of time than scaling a monolithic application under the same conditions scaling.

Machine Learning at the Mobile Edge: The Case of Dynamic Adaptive Streaming Over HTTP (DASH)

Dynamic Adaptive Streaming over HTTP (DASH) is a standard for delivering video in segments and adapting each segment’s bitrate (quality), to adjust to changing and limited network bandwidth. We study segment prefetching, informed by machine learning predictions of bitrates of client segment requests, implemented at the network edge. We formulate this client segment request prediction problem as a supervised learning problem of predicting the bitrate of a client’s next segment request, in order to prefetch it at the mobile edge, with the objective of jointly improving the video streaming experience for the users and network bandwidth utilization for the service provider. The results of extensive evaluations showed a segment request prediction accuracy of close to 90% and reduced video segment access delay with a cache hit ratio of 58%, and reduced transport network load by lowering the backhaul link utilization by 60.91%.

Захист відкритих клієнтів за допомогою одного алгоритму авторизації

The paper focuses on authorization in public clients and provides a secure authorization model as an alternative to costly Microsoft Duende BFF solution. After providing a brief overview of confidential and public clients in terms of authorization, we have analyzed problems and potential attack vectors associated with the authorization process in public clients due to their inability to hold credentials securely. Confidential clients are implemented on secure servers or able to facilitate secure authentication by other means, while public clients lack this security. Our research discovered algorithms, models, and methods for secure authorization in public clients. As a part of our model, we have implemented high entropy Proof Key for Code Exchange generator in C# .NET 6.0. In addition, we have provided a solution to a problem of storing sensitive information in public clients using the Backend for Frontend concept. This concept leverages a reverse proxy pattern where a backend application acts as a proxy and handles all client requests. Having a proxy backend application significantly tightens security model for public clients, while restricting possible attack vectors. The authorization model being researched was based on Proof Key for Code Exchange and Backend for Frontend approach. During the testing phase of our research, we have confirmed that the model was not vulnerable to Cross-Site-Scripting and Auth Code Interception attacks. A sequence diagram outlining main actors and interactions among them in context of authorization has been designed. The diagram stands as the visual representation of the model that uses proposed methods and algorithms. As a result, we have managed to build an alternative to secure authorization solutions for public clients that do not rely on the client secret. We have summarized our key findings in a Blazor Web Assembly application, which is classified as public and uses the described authentication model.

Stochastic coordination in heterogeneous load balancing systems

Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically arrive at multiple entry points, and dispatching them to servers is an urgent distributed systems problem. This paper presents an efficient solution to the load balancing problem in such systems that improves on and overcomes problems of previous solutions. The load balancing problem is formulated as a stochastic optimization problem, and an efficient algorithmic solution is obtained based on a subtle mathematical analysis of the problem. Finally, extensive evaluation of the solution on simulated data shows that it outperforms previous solutions. Moreover, the resulting dispatching policy can be computed very efficiently, making the solution practically viable.

Performance Analysis of Openlitespeed and Apache Web Servers in Serving Client Requests

<p class="Abstract">Web server those who use apache are now very familiar to users, because apache is easier to use than other web servers, but runs PHP applications (Hypertext Preprocessor) by handling 100000 requests is certainly very influential on the speed of the web server. Openlitespeed is a web server that functions the same as apache, but server users are more likely to use openlitespeed. This study conducted a performance test on both web servers to find out which web server is very suitable for use in completing client requests. This test uses the https://webpagetest.org, https://gtmetrix.com and https://developers.google.com/speed/pagespeed/insights applications. To do benchmarking of the many diverse client requests. The trial results in the current study provide benchmarking results which result in terms of time usage.</p>

Application of Clustering Method For Customer Royal Data Grouping at CV. Garuda Mas Motor Binjai

Communication is a very important activity. Communication is carried out with the aim of exchanging information between several individuals. Communication can be done in various ways. Those who wish to communicate with each other can meet in person or through intermediaries. There are several types of media that function as intermediaries of information. You can use several media such as print media, electronic media, and online media to get various information. Digital communication in the modern era is not far from the Internet because almost all digital communication tools use the Internet. Internet needs vary greatly from old to young, because Internet needs are different, connection management is needed (Management Bandwidth) so that client requests with high connections do not interfere with clients with relatively low connection requests. One of the tools commonly used for connection management is MikroTik with the Peer Connection Queue (PCQ) feature. The reason for choosing Mikrotik is because Mikrotik has complete features at an affordable price. The importance of connection management is to maximize the connection provided by the ISP so that clients can use the Internet without buffering.

Performance Enhancement of Cloud Datacenters Through Replicated Database Server

Cloud computing has risen as a new computing paradigm providing computing, resources for networking, and storage as a service across the network. Data replication is a phenomenon which brings the available and reliable data (e.g., maybe the databases) nearer to the consumers (e.g., cloud applications) to overcome the bottleneck and is becoming a suitable solution. In this paper, the authors study the performance characteristics of a replicated database in cloud computing data centres which improves QoS by reducing communication delays. They formulate a theoretical queueing model of the replicated system by considering the arrival process as Poisson distribution for both types of client request, such as read and write applications. They solve the proposed model with the help of the recursive method, and the relevant performance matrices are derived. The evaluated results from both the mathematical model and extensive simulations help to study the unveil performance and guide the cloud providers for modelling future data replication solutions.

A Journey Into the Unknown: PhD Students in a European Training Network on Age-related Changes in Hematopoiesis Conduct Their Project During a Global Pandemic

A Journey Into the Unknown: PhD Students in a European Training Network on Age-related Changes in Hematopoiesis Conduct Their Project During a Global Pandemic

Bandwidth Management and Web Filtering with Per Connection Queue (PCQ) Method using Microtik

Communication is a very important activity. Communication is carried out with the aim of exchanging information between several individuals. Communication can be done in various ways. Those who wish to communicate with each other can meet in person or through intermediaries. There are several types of media that function as intermediaries of information. You can use several media such as print media, electronic media, and online media to get various information. Digital communication in the modern era is not far from the Internet because almost all digital communication tools use the Internet. Internet needs vary greatly from old to young, because Internet needs are different, connection management is needed (Management Bandwidth) so that client requests with high connections do not interfere with clients with relatively low connection requests. One of the tools commonly used for connection management is MikroTik with the Peer Connection Queue (PCQ) feature. The reason for choosing Mikrotik is because Mikrotik has complete features at an affordable price. The importance of connection management is to maximize the connection provided by the ISP so that clients can use the Internet without buffering.

Universal CMAF Container for Efficient Cross-Format Low-Latency Delivery

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Current implementations of low-latency adaptive streaming over HTTP utilize a diversity of presentation formats, containers, origins, and caching behaviors. For efficient delivery, a common origin and a single set of cacheable media objects provide the highest performance and scalability across a delivery system. This article introduces a means of leveraging the Common Media Application Format (CMAF) as a standardized container format, combined with specific content encoding constraints and addressing mode constraints in low-latency HTTP Live Streaming (HLS) (LL-HLS) and low-latency Dynamic Adaptive Streaming over HTTP (DASH) (LL-DASH), to provide a cross-format solution that maximizes edge cache efficiency and minimizes origin storage costs and client request rate</i> .

Social Media Affect on Contemporary Design for Architect and Client via Instagram Sites

The development of information technology, especially social media, not only has an impact on changing the behavior of its users, but also brings changes in various fields. The high intensity of human activity on social media can no doubt change the lifestyle of its users, including influencing the design of their dwellings. This phenomenon is expected to be used especially for architects to open up new opportunities in getting their clients. This study uses a qualitative method with a library research approach. This study displays scientific reasoning related to the development of social media which can have an impact on changes in work process patterns and the final result of a contemporary design work in the world of architecture. Like a client's request who plans a contemporary residential design following trends on social media, one of which is Instagram. Instagram is the third most used social media platform in the world. This is very effective for architects and prospective clients by utilizing social media to see references to the design of the building they want to plan. It is certain that the rapid development of social media information technology, especially Instagram, can affect the world of residential design.

On Mixing Eventual and Strong Consistency: Acute Cloud Types

In this article we study the properties of distributed systems that mix eventual and strong consistency. We formalize such systems through <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">acute cloud types</i> (ACTs), abstractions similar to conflict-free replicated data types (CRDTs), which by default work in a highly available, eventually consistent fashion, but which also feature strongly consistent operations for tasks which require global agreement. Unlike other mixed-consistency solutions, ACTs can rely on efficient quorum-based protocols, such as Paxos. Hence, ACTs gracefully tolerate machine and network failures also for the strongly consistent operations. We formally study ACTs and demonstrate phenomena which are neither present in purely eventually consistent nor strongly consistent systems. In particular, we identify <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">temporary operation reordering</i> , which implies interim disagreement between replicas on the relative order in which the client requests were executed. When not handled carefully, this phenomenon may lead to undesired anomalies, including circular causality. We prove an impossibility result which states that temporary operation reordering is unavoidable in mixed-consistency systems with sufficiently complex semantics. Our result is startling, because it shows that apparent <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">strengthening</i> of the semantics of a system (by introducing strongly consistent operations to an eventually consistent system) results in the weakening of the guarantees on the eventually consistent operations.

Accelerating Reads With In-Network Consistency-Aware Load Balancing

We present FLAIR, a novel approach for accelerating read operations in leader-based consensus protocols. FLAIR leverages the capabilities of the new generation of programmable switches to serve reads from follower replicas without compromising consistency. The core of the new approach is a packet-processing pipeline that can track client requests and system replies, identify consistent replicas, and at line speed, forward read requests to replicas that can serve the read without sacrificing linearizability. An additional benefit of FLAIR is that it facilitates devising novel consistency-aware load balancing techniques. Following the new approach, we designed FlairKV, a key-value store atop Raft. FlairKV implements the processing pipeline using the P4 programming language. We evaluate the benefits of the proposed approach and compare it to previous approaches using a cluster with a Barefoot Tofino switch. Our evaluation indicates that, compared to state-of-the-art alternatives, the proposed approach can bring significant performance gains: up to 42% higher throughput and 35–97% lower latency for most workloads. Furthermore, our evaluation shows that our novel load balancing techniques can cope with heterogeneous load and hardware to achieve higher performance, and that FLAIR can scale to support large data sets and clusters.

Leader Confirmation Replication for Millisecond Consensus in Private Chains

The private chain-based Internet-of-Things (IoT) system ensures the security of cross-organizational data sharing. As a widely used consensus model in private chains, the leader-based state-machine replication (SMR) model meets the performance bottleneck in IoT blockchain applications, where nontransactional sensor data are generated on a scale. We analyzed IoT private chain systems and found that the leader maintains too many connections due to high latency and client request frequency, which results in lower consensus performance and efficiency. To meet this challenge, we propose a novel solution for maintaining low request latency and high transactions per second (TPS): replicate nontransactional data by followers and confirm by the leader to achieve nonconfliction SMR, rather than all by the leader. Our solution, named leader confirmation replication (LCR), uses the newly proposed future log and confirmation signal to achieve nontransactional data replication on the followers, thereby reducing the leader’s network traffic and the request latency of transactional data. In addition, the generation replication strategy is designed to ensure the reliability and consistency of LCR when meeting membership changes. We evaluated LCR with various cluster sizes and network latencies. The experimental results show that in ms-network latency (2–30) environments, the TPS of LCR is 1.4X-1.9X higher than Raft, the transactional data response time is reduced by 40%–60%, and the network traffic is reduced by 20%–30% with acceptable network traffic and CPU cost on the followers. In addition, LCR shows high portability and availability since it does not change the number of leaders or the election process.

Задача анализа эмоциональной окраски текстов в банковской деятельности

The paper presents the author's approach to solving the problem of sentiment analysis of online Russian-language messages about the activities of banks. The study data are customer reviews about banks in general and their products, services and quality of service posted on the Banki.ru portal. In this paper, the problem of text sentiment analysis is considered as a binary classification task based on a set of positive and negative reviews. A vector model with a tf-idf weighting scheme was used to represent the collected and preprocessed texts. The following algorithms with the selection of optimal parameters on the grid were used for binary classification task: naive Bayesian classifier, support vector machine, logistic regression, random forest and gradient boosting. Standard statistical metrics, such as accuracy, completeness, and F-measure, were used to evaluate the quality of solving the classification problem. For the indicated metrics, the best results were obtained on the classification model developed with the use of Support Vector Machine. Thematic text modeling was also carried out using the Dirichlet latent placement method to define the most typical topics of customer messages. As a result, it was concluded that the most popular message topics are "cards" and "quality of service". The obtained results can be used in the activities of banks to automate its reputation monitoring in the media and when routing client requests to solve various problems. When solving problems, the features of the Python programming language were actively used, namely, libraries for web scraping, machine learning, and natural language processing.

Raft-PLUS: Improving Raft by Multi-Policy Based Leader Election with Unprejudiced Sorting

Raft is a fast, scalable, understandable consensus algorithm widely used in distributed systems. The Leader handles client requests and interacts with other servers to reach a consensus, so a stable, reliable, and powerful Leader is crucial for the cluster. We designed a policy-based voting mechanism to make the elected Leader as reliable as possible. In order to improve the asymmetric relationship between the Followers and Leader, we designed a mechanism to trigger a new round of the election actively so that the Leader node can actively transform into a Follower under certain conditions and enhance the symmetry between servers. Our proposed Raft-PLUS algorithm makes the elected Leader as reliable as possible through four election policies and designed three opposition policies to trigger a new round of the election. To verify the effectiveness of the Raft-PLUS algorithm, we configure different election and opposition policies on 12 servers to simulate the election and opposition process of the Leader and explain the process. To demonstrate the advantages of the Raft-PLUS algorithm, we built key-value stores based on Raft and Raft-PLUS, and we tested the performance of Raft-PLUS and the Raft algorithm in normal and abnormal states. Experimental results show that the Raft-PLUS algorithm has similar write throughput to the Raft algorithm under normal conditions. Regarding the quality of the Leader network changes, the average write throughput of the Raft-PLUS algorithm is 40% higher than that of the Raft algorithm. The Leader’s CPU usage fluctuated; the average write throughput of Raft-PLUS was 38% higher than Raft.

Enhancing Response Time of Cloud Resources Through Energy Efficient Cloud Scheduling Algorithm

Cloud Computing is becoming a dominant trend in providing information technology (IT) services. The cloud comprises many hardware and software resources today, and more people are switching to such services. Users' requests for cloud resources must incur a minimum amount of load on the system while getting a rapid response. In the cloud today, there is too much computational power. Load balancing makes it possible for various components of the cloud computing environment to work efficiently. To balance client requests to available resources so that the system is not overloaded, and the requested resources are delivered as quickly as possible, an effective load balancing strategy is essential. In this research article, we have presented a critical analysis of various existing cloud load balancing and scheduling algorithms. Several task scheduling approaches have been proposed in the literature review, but there appears to be a lack of scheduling algorithms for real-time task works based on historical scheduling records (HSR). The proposed algorithm uses information available in HSR to efficiently distributes incoming user requests to available virtual machines. The proposed scheduling algorithm uses the scaleup and scale down resource algorithm which helps in achieving maximum resource utilization. The algorithm tries to balance the load on VMs by scaling up and down cloud resources. WorkflowSim is used to analyze the performance of the algorithm proposed. The simulation results are compared with the existing scheduling algorithm which shows the proposed algorithm outperforms existing scheduling algorithms in terms of makespan.