Advanced Software Technologies Research Articles

Blockchain-inspired intelligent framework for logistic theft control

The smart logistics industry utilizes advanced software and hardware technologies to enhance efficient transmission. By integrating smart components, it identifies vulnerabilities within the logistics sector, making it more susceptible to physical attacks aimed at theft and control. The main goal is to propose an effective logistics monitoring system that automates theft prevention. Specifically, the suggested model analyzes logistics transmission patterns through secure surveillance enabled by IoT-based blockchain technology. Additionally, a bi-directional convolutional neural network is employed to evaluate real-time theft vulnerabilities, aiding optimal decision-making. The proposed method has been shown to provide accurate real-time analysis of risky behaviors. Experimental simulations indicate that the proposed solution significantly improves logistics monitoring. The system’s performance is assessed using various statistical metrics, including latency rate (7.44 s), a data processing cost (O((n−1)logn)), and model training and testing results (precision (94.60%), recall (95.67%), and F-Measure (96.64%)), statistical performance (error reduction (48%)) and reliability (94.48%).

Business chatbots with deep learning technologies: state-of-the-art, taxonomies, and future research directions

With the support of advanced hardware and software technology, Artificial Intelligence (AI) techniques, especially the increasing number of deep learning algorithms, have spawned the popularization of online intelligent services and accelerated the contemporary development and applications of chatbot systems. The promise of providing 24/7 uninterrupted business services and minimizing workforce costs has made business chatbots a hot topic due to the impact of the pandemic. It has attracted considerable attention from academic researchers and business practitioners. However, a thorough technical review of advanced chatbot technologies and their relevance and applications to various business domains is rare in the literature. The main contribution of this review article is the critical analysis of various chatbot development approaches and the underlying deep learning computational methods in the context of some business applications. We first conceptualize current business chatbot architectures and illustrate the technical characteristics of two common structures. Next, we explore the mainstream deep learning technologies in chatbot design from the perspective of computational methods and usages. Then, we propose a new framework to classify chatbot construction architectures and differentiate the traditional retrieval-based and generation-based chatbots in terms of the modern pipeline and end-to-end structures. Finally, we highlight future research directions for business chatbots to enable researchers to devote their efforts to the most promising research topics and commercial scenarios and for practitioners to benefit from realizing the trend in business chatbot development and applications.

107 A pragmatic approach to portable neuroimaging utilized in clinical research

OBJECTIVES/GOALS: The aim of thispaper is to raise awareness of the limitations of the current pMRI training paradigm and to recommend a standardization of skills to expand diversity among field-based neuroimaging technicians. METHODS/STUDY POPULATION: Currently, there are seven international brain research initiatives. The goal is to establish and understand the cultural values a society holds and how the outcomes of research may be adopted into societal practice. We must also consider the benefits of early detection amongst minoritized communities in neuroscience research. Neuroimaging in remote settings can allow patients to advocate more accurately for timely medical care which can lead to better health outcomes. According to the Journal of Neurological Sciences, neuroscience accounts for 9% of total medical publications. RESULTS/ANTICIPATED RESULTS: Neuroimaging research continues to evolve in terms of resolution and portability. T By harnessing diverse data, we are able to utilize advanced neuroimaging techniques and software technology to recognize trends amongst subgroups of individuals who were previously considered geographically inaccessible. DISCUSSION/SIGNIFICANCE: Despite the excitement and promise of portable neuroimaging devices, there is a fundamental need to establish standardized training procedures that can be accessed by individuals of all socioeconomic backgrounds.

GPT-Empowered Personalized eLearning System for Programming Languages

The eLearning approach to programming language instruction has gained widespread acceptance due to advantages such as accessibility, temporal flexibility, and content reusability. However, the current eLearning for programming predominantly employs the delivery of one-size-fits-all content, engendering elevated costs in both the development of language coursework and administration of eLearning sessions, which includes the labor-intensive task of grading student submissions. A compelling research question to consider is how to construct an eLearning system capable of delivering personalized, student-centric content, automating the generation of coursework elements, and eliminating the need for instructor involvement in the management of eLearning sessions. Our approach to delivering a definite solution to the question involves the utilization of a suite of advanced software technologies: GPT to dynamically generate course contents/components, prompt engineering to personalize course content for each individual student, and autonomous computing to manage eLearning sessions without the need for human intervention. The research results encompass the design of an eLearning framework covering all programming languages, a fully functional Python-based implementation, seamless integration with ChatGPT for dynamic content generation, a high degree of content personalization, and the elimination of manual effort required for managing eLearning sessions.

Вызовы в реализации систем глубокого анализа сетевого трафика методом полного протокольного декодирования

This paper presents a summary of experience in developing the deep packet inspection system using full protocol decoding. The paper reviews the challenges encountered during implementation and provides a high-level overview of the solutions to these issues. The challenges can be grouped into two groups. The first group is related to the fundamental tasks which must be addressed when implementing full protocol decoding systems. This includes ensuring correct protocol parsing, which involves identifying and interpreting protocol headers and fields correctly. Moreover, it is necessary to ensure the processing of fragmented packets and the assembly of fragments into the original message. Additionally, the processing and analysis of encrypted traffic is a crucial task that may require the use of specialized algorithms and tools. The second group of problems is related to optimizing the process of full protocol decoding to ensure high-speed traffic processing, as well as supporting new protocols and the ability to add user-defined extensions. While there are open-source systems that address some of the primary issues associated with full protocol decoding, there may be a need for additional effort and specialized solutions to efficiently operate and expand the functionality of such systems. Although implementing deep network traffic analysis tools using full protocol decoding requires the use of advanced hardware and software technologies, the benefits of such analysis are significant. This approach provides a more complete understanding of network traffic patterns and enables more effective detection and prevention of cyber-attacks. It also allows for more accurate monitoring of network performance and the identification of potential bottlenecks or other issues that may impact network efficiency. In this article, we also emphasize the importance of system architecture development and implementation to ensure the successful deployment of deep network traffic analysis tools using full protocol decoding. At last, we conducted an experiment where several advanced optimizations were implemented in the system that had already solved primary issues. These optimizations related to working with memory, based on the features of the traffic processing scheme. By results, we evaluated significant performance improvement in solving secondary tasks, described in this work.

Using social media analysis to study population dietary behaviours: A scoping review.

The rapid adoption and sustained use of social media globally has provided researchers with access to unprecedented quantities of low-latency data at minimal costs. This may be of particular interest to nutrition research because food is frequently posted about and discussed on social media platforms. This scoping review investigates the ways in which social media is being used to understand population food consumption, attitudes and behaviours. The peer-reviewed literature was searched from 2003 to 2021 using four electronic databases. The review identified 71 eligible studies from 25 countries. Two-thirds (n = 47) were published within the last 5 years. The USA had the highest research output (31%, n = 22) and Twitter was the most used platform (41%, n = 29). A diverse range of dataset sizes were used, with some studies relying on manual techniques to collect and analyse data, whereas others required the use of advanced software technology. Most studies were conducted by disciplines outside health, with only two studies (3%) being conducted by nutritionists. It appears the development of methodological and ethical frameworks as well as partnerships between experts in nutrition and information technology may be required to advance the field in nutrition research. Moving beyond traditional methods of dietary data collection may prove social media as a useful adjunct to inform recommended dietary practices and food policies.

PENGEMBANGAN POLYCLINIC MOBILE APPLICATION UNTUK MENINGKATKAN PELAYANAN KESEHATAN PADA MASYARAKAT PEKERJA

The use of mobile devices is increasingly popular. Mobile devices are increasingly equipped with advanced hardware and software technology. With dynamic performance and practical on mobile devices can master the development of the world ICT industry (information and communication technology). Software has become one of the spearheads of mobile success device. The creation of application programs is an important breakthrough in mobile development device. Likewise, the development of the Polyclinic Mobile Application in lecturer research This beginner is to provide solutions to problems that exist at the polyclinic at environment of PT. Eka Sandang Duta Prima Semarang, which is not yet supported by ICT, so in providing health services to the community, workers who are less than optimal can resolved. In developing the Polyclinic Mobile Application, it is not only a registration feature only, but there are several other features that were developed such as; polyclinic profile, schedule practice, modern queuing system, recording medical records, view patient history, take notes medical action, noting the drug administered.

Paradoxical Temporal Enlargement: An Expansion of Superficial Temporal Fat Pad Following Interfacial Technique for Pterional Craniotomy.

Contour irregularities in the temporal region have been reported previously after procedures involving temporal dissection. In this study, we report paradoxical temporal enlargement (PTE) following interfascial pterional craniotomy. A retrospective review of patients who underwent a unilateral transcranial procedure with frontotemporal approach at our institution between September 2013 and December 2017 was performed. Patients with a previous craniotomy or bilateral craniotomy were excluded. Radiological imaging series including computed tomography and magnetic resonance imaging were utilized to calculate temporal soft tissue volumes both preoperatively and postoperatively by using advanced software technology. Relative soft tissue volume differences between the operative side and the contralateral side were calculated at different time-points including preoperative, 3-months follow-up (3M), 12-months (12M) follow-up, and the last follow-up (LFU, over 1-year). Forty-three patients were included. Mean age was 52.7 ± 4.5 years. Mean follow-up was 27.9 ± 15.8 months. Significant changes of temporal fat pad relative-volume difference were observed between the preoperative and the corresponding 3M (t [82] = -2.8865, P = 0.0050); 12M (t [77] = -4.4321, P < 0.0001), and LFU (t [74] = -4.9862, P < 0.0001) postoperative time points. No significant change of the temporalis muscle was observed between the preoperative and the corresponding 3M (P = 0.3629), 12M (P = 0.1553), or LFU (P = 0.0715). Soft tissue volume showed a significant increase on the operative side between the preoperative and the corresponding LFU (t [74] = -2.5866, P = 0.0117). Paradoxical temporal enlargement with more than 10% volumetric change was observed in 24% of the patients at their LFU (>1-year). This change was not due to temporalis muscle changes. Paradoxical temporal enlargement was due to hypertrophy of the superficial temporal fat pad. Before surgical correction of postoperative temporal contour changes, it is important to obtain imaging and characterize the etiology of the deformity.

Design and development of multi tenancy security issues in cloud computing

With the advent of technology cloud computing has become the next generation of network computing where cloud computing can deliver both software and hardware as on-demand services over the Internet. Cloud computing has enabled small organizations to build web and mobile apps for millions of users by utilizing the concept of “pay-as-you-go” for applications, computing, network and storage resources as on-demand services. These services can be provided to the tenants in different categories: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). In order to decrease the costs for the cloud users and increase resource utilization, cloud providers try to share the resources between different organizations (tenants) through a shared environment which is called Multi-Tenancy. Even though multi-tenancy’s benefits are tremendous for both cloud providers and users, security and privacy concerns are the primary obstacles to Multi- Tenancy. Since Multi-Tenancy dramatically depends on resource sharing, many experts have suggested different approaches to secure Multi-Tenancy. One of the solutions is resource allocation and isolation techniques. In most cases, resource allocation techniques consider but are not sufficient for security. OpenStack community uses a method to isolate the resources in a Multi-Tenant environment. Even though this method is based on a smart filtering technique to segregate the resources in Compute nodes (the component that the instances are running on it in OpenStack), this method is not flawless. The problem comes up in the Cinder nodes where the resources are not isolated. This failure can be considered as a security concern for a Multi- Tenant environment in OpenStack. In order to solve this problem, this system explores a method to secure Multi- Tenancy for both sides in the Compute node and for backend where Block Storage devices for the instances can be isolated as well and with advanced software technologies and will address the societal changes due to cloud computing.

AGTECH – THE AGRICULTURE OF 21 CENTURE

Aims. Presentation of the perspectives facing technological agriculture nowadays. The industry that is least digitalized is turning agriculture into an unattractive investment field for innovative entrepreneurs. Through the activities that technology can and does apply in agriculture, it is believed that it can be technically supported to a stage where it provides more and better quality products. Materials and methods. Literary review of current information about the new generation of agriculture. Results. A brief overview of the current concept of agtech in agriculture. Conclusion. The concept of AgTech is an innovative symbiosis between agriculture and technology. The technological concept is developing in the modern entrepreneurial environment, turning agriculture into an attractive area for young entrepreneurs. The combination of specific advanced software or hardware technology in the agricultural chain leads to an improvement in agricultural production. AgTech is an industry that includes a variety of solutions for almost every step in the food production process. The goal of technological innovation is to reach levels with the production of sustainable agriculture.

Improving the Correctness of Medical Diagnostics Based on Machine Learning With Coloured Petri Nets

Advanced software and storage technologies have enabled medical facilities to record and store vast amounts of data about cancer patients. There is a strong demand for an accurate and interpretable method to perform cancer prognostic for effective treatment. Machine learning algorithms, undoubtedly, demonstrate a remarkable ability to recognize models and extract patterns from data to improve medical prognosis decision-making. But machine learning outcomes are prone to bias and inaccurate labelling. Therefore, to negate the impact of such errors in the prognostic decision-making process, the mechanism to correct such errors is in high demand. This article addresses this problem by proposing the use of Coloured Petri nets formalism to ensure the correctness of the machine learning based prognostic process. Use of formalism makes it possible to ensure that prognostic decisions are correct and understandable. Empirical results show that we have increased the accuracy of prognostic decisions by up to 90%. This research supports improved prognostic decision-making for the effective treatment and identification of cancer patients.

Recent Advances and Trends in Microfluidic Platforms for C. elegans Biological Assays

Microfluidics has proven to be a key tool in quantitative biological research. The C. elegans research community in particular has developed a variety of microfluidic platforms to investigate sensory systems, development, aging, and physiology of the nematode. Critical for the growth of this field, however, has been the implementation of concurrent advanced microscopy, hardware, and software technologies that enable the discovery of novel biology. In this review, we highlight recent innovations in microfluidic platforms used for assaying C. elegans and discuss the novel technological approaches and analytic strategies required for these systems. We conclude that platforms that provide analytical frameworks for assaying specific biological mechanisms and those that take full advantage of integrated technologies to extract high-value quantitative information from worm assays are most likely to move the field forward.

Applications of Pathology-Assisted Image Analysis of Immunohistochemistry-Based Biomarkers in Oncology

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

Hierarchical Bounding Sphere FFD-AABB Algorithm for Fast Collision Handing of 3D Deformable Objects on Smart Devices

Due to the recent enriched micro-level hardware and advanced computer software technology, portable yet powerful smart devices draw fervent responses from users and consequently the world’s smart device market has been rapidly expanded. In addition, since smart devices can be used anytime and anywhere using the wireless internet environment, the traditional PC-oriented works are swiftly moving to smart devices. Recently, the demands for representing more realistic 3D deformable objects have been increased for smart device based 3D game, virtual reality, 3D mobile advertisement, augmented reality and so on. However, current smart devices cannot sufficiently process the details of complex 3D object representation and associated physics based animation yet. This paper proposes a new optimized 3D object simulation and collision handling method specifically targeted for smart devices. The proposed hierarchical bounding sphere FFD- AABB (Free Form Deformation -- Axis Aligned Bounding Box) algorithm provides efficient 3D object simulation, since it quickly rejects unnecessary complex collision tasks by executing simple hierarchical bounding sphere distance tests. We have conducted experimental tests under various iOS environments and have performed comparative performance analysis with previous methods. The proposed method shows on average 34% improvement in dynamic simulation and collision handling procedures.

Research on Avatar-Included Virtual Environment Modeling and Testing

It is possible to model and evaluate avatar-included virtual environment in the condition of advanced hardware and software technologies of digital 3D. In traditional design and evaluation, there is no interaction between digital virtual scene and avatars, and no dynamic modifying options for virtual scene. Interaction and dynamic design option are the most important functions for virtual reality simulation. The paper presented the modeling method of avatar-included virtual scene first, discussed the method of testing and evaluating for it secondly. The research can assist and support realization of avatar-included virtual scene real-time interaction, testing and evaluating for stability, security and humanoid.

Flexible load shedding strategy considering real‐time dynamic thermal line rating

In recent years, real-time dynamic thermal line rating (RT-DTLR) technology has been developed and implemented in operations to improve transmission line capacity, so that congestion costs and/or risk of load shedding can be reduced. Power systems obviously benefit from this technology but also bear the risks because of thermal overload of transmission lines. To involve RT-DTLR technology into conventional power system load shedding strategies, this study explains the concept of flexibility in power system analysis, expresses transmission line capacity constraints into flexible forms and proposes a flexible load shedding strategy considering RT-DTLR. The two sub-objective functions, representing load shedding quantity and system risk increment, are normalised and expressed as the confidence levels from system security consideration and load loss consideration, respectively. The proposed method takes advantage of both the advanced hardware and software technologies in smart grids and the simulation results showed that it can trade off the benefits and risks brought about by RT-DTLR in load shedding.

A New Automotive Electronic Control System Open Architecture

Considering the shortcomings of close car E/E control system, through the analysis of the open system requirements and characteristics of the car E/E control system, an open system structure of the automotive electronic control system based on quantum framework established/E adopts advanced software technology of embedded system. The electronic control clutch design experiments show that the system can get open role use style of the building and system based on this architecture more than a closed system.

Applications of advanced data analysis and expert system technologies in the ATLAS Trigger-DAQ Controls framework

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment is a very complex distributed computing system, composed of more than 20000 applications running on more than 2000 computers. The TDAQ Controls system has to guarantee the smooth and synchronous operations of all the TDAQ components and has to provide the means to minimize the downtime of the system caused by runtime failures. During data taking runs, streams of information messages sent or published by running applications are the main sources of knowledge about correctness of running operations. The huge flow of operational monitoring data produced is constantly monitored by experts in order to detect problems or misbehaviours. Given the scale of the system and the rates of data to be analyzed, the automation of the system functionality in the areas of operational monitoring, system verification, error detection and recovery is a strong requirement. To accomplish its objective, the Controls system includes some high-level components which are based on advanced software technologies, namely the rule-based Expert System and the Complex Event Processing engines. The chosen techniques allow to formalize, store and reuse the knowledge of experts and thus to assist the shifters in the ATLAS control room during the data-taking activities.

Keeping the Sickest Patients Safer: Telemedicine and Critical Care

Telemedicine in critical care offers opportunities to improve quality and safety by connecting bedside care teams with off-site tele-ICU staff using advanced software and continuous remote monitoring technology. This leads to more proactive care, fewer complications, and timely decisions regarding care.

Flexible software architecture and language for mobile agents

SUMMARYIn this paper, we present a flexible software architecture and a language for systems of mobile agents starting from a formalism with timed interactions and explicit locations. The language supports the specification of a distributed system, that is, agents and their physical distribution, and allows a timed migration in a distributed environment. Advanced software technologies are used to define the software architecture and the agents language, facilitating also the agents development. We illustrate the system by a dynamic network discovery in which the agents take into account the latency and the CPU load when choosing where to migrate. Copyright © 2011 John Wiley &amp; Sons, Ltd.