Smooth Data Flow Research Articles

Global sustainable closed-loop supply chain considering Incoterms rules and advertisement impacts

Industrial information integration plays a crucial role in modern supply chains by ensuring the smooth flow of data across all stages, including recovery, recycling, and disposal, which is essential for the successful implementation of a closed-loop supply chain (CLSC) model. Building on this, our paper addresses a global CLSC problem by incorporating International Commercial Terms (Incoterms) and international transportation modes, bridging global supply chain operations with sustainability criteria. This innovative approach advances the development of a globally sustainable CLSC by focusing on the integration of economic, environmental, and social factors, i.e., the triple bottom line of sustainability. Specifically, we address environmental concerns through the introduction of carbon taxation and enhance social sustainability by exploring the impact of advertising on customer satisfaction. To further refine this model, we classify customers based on their sustainability engagement and apply a fuzzy programming approach to account for uncertainty in customer demand influenced by advertising. To solve this complex global CLSC model, we conduct a thorough analysis of constraints and develop a robust Lagrangian relaxation reformulation. While the initial solution may result in infeasibility, we propose a heuristic algorithm that ensures feasible solutions. Our efficient Lagrangian-based heuristic, incorporating an adaptive strategy, is capable of solving large-scale networks with an approximate 10% optimality gap. Ultimately, this research provides both a comprehensive framework for practitioners to improve the environmental performance and global operations of their supply chains, as well as significant theoretical contributions to the field of industrial information systems.

An Interactive Multi-Modal Query Answering System with Retrieval-Augmented Large Language Models

Retrieval-augmented Large Language Models (LLMs) have reshaped traditional query-answering systems, offering unparalleled user experiences. However, existing retrieval techniques often struggle to handle multi-modal query contexts. In this paper, we present an interactive M ulti-modal Q uery A nswering (MQA) system, empowered by our newly developed multi-modal retrieval framework and navigation graph index, integrated with cutting-edge LLMs. It comprises five core components: Data Preprocessing, Vector Representation, Index Construction, Query Execution, and Answer Generation, all orchestrated by a dedicated coordinator to ensure smooth data flow from input to answer generation. One notable aspect of MQA is its utilization of contrastive learning to assess the significance of different modalities, facilitating precise measurement of multimodal information similarity. Furthermore, the system achieves efficient retrieval through our advanced navigation graph index, refined using computational pruning techniques. Another highlight of our system is its pluggable processing framework, allowing seamless integration of embedding models, graph indexes, and LLMs. This flexibility provides users diverse options for gaining insights from their multi-modal knowledge base. A preliminary video introduction of MQA is available at https://youtu.be/xvUuo2ZIqWk.

Enhancing cancer detection through AI-driven high content analysis of circulating tumor cells.

3054 Background: The advancements in automated High Content Analysis (HCA) for Circulating Tumor Cells (CTCs) detection necessitate the integration of high-throughput screening (HTS) and Artificial Intelligence (AI) to improve cancer diagnosis efficiency and accuracy. Traditional approaches to cancer detection have faced limitations in speed, cost, and analysis depth, driving the need for innovative solutions in assay development and execution. Methods: We obtained peripheral blood from 150 asymptomatic individuals and 63 newly diagnosed cases of solid organ cancers including Lung, Breast, Head and Neck, Colorectal, Pancreas, Esophagus, Gynecologic cancers. We used differential apoptosis based negative enrichment technique and HCS fluorescent imaging for identification of CTCs and CTC like immune cells from the relevant blood samples. We devised AutoML algorithms which were trained on a cohort of 4,135 cropped region of interest (ROI) images of true CTCs and CTC-mimicking immune cells. These images were annotated with the coordinates of the top-left and bottom-right corners of rectangles to specify ROIs. This method employs a combination of automated sample processing, integration with the Laboratory Information Management System (LIMS) integration, digital filtration, and decision matrix algorithms for sample classification and smooth data flow. The image quality criteria were established prior to dataset analysis. The algorithms underwent training, testing, and validation based on expert recommendations, with dataset splitting of 80% for training, 10% for testing, and 10% for validation phases. Results: The automated deep learning model achieved remarkable performance metrics, presenting an accuracy of 96.66% (95% CI, 96.07%-97.19%), a specificity of 95.34% (95% CI, 94.37%-96.18%), and a sensitivity of 98.14% (95% CI, 97.44%-98.69%) in detecting true CTCs. Additional analysis included the area under the curve and confusion matrix evaluations, indicating the model's robustness in distinguishing between true positive and true negative specimens. This efficiency and precision in data handling, processing, and analysis demonstrate significant advancements in HCA screening, offering enhanced assay development, execution flexibility, and the facilitation of detailed cell-by-cell analysis for cancer detection from a large set of Peripheral Blood Mononuclear Cells (PBMCs) from samples obtained for screening or diagnosis. Conclusions: This study successfully evaluated a deep learning model for the detection of circulating tumor cells (CTCs) in peripheral blood mononuclear cells (PBMCs) using image data from HTS platform. The model achieved superior performance, demonstrating its potential for cancer detection from blood samples.

Courier Service System

The demand for efficient courier services is growing rapidly, and traditional systems often struggle to meet these demands. This project introduces an Enhanced Courier Service System Application, utilizing cutting-edge technologies such as ReactJS for the frontend, Java Spring Boot for the backend, and MongoDB for the database. The primary objective is to develop a robust and scalable courier service system that offers enhanced features and functionalities to meet the evolving needs of users. The system architecture facilitates seamless communication between frontend, backend, and database components, ensuring smooth data flow and efficient processing. ReactJS for the frontend enhances user experience, while Java Spring Boot provides scalability, security, and performance. MongoDB, a NoSQL database, offers flexibility and scalability for large data storage and retrieval. The modular design allows for easy maintenance and future enhancements, adapting to changing requirements and technologies. By incorporating industry-standard practices like UML diagrams, data flow diagrams, and sample test cases, the project aims to deliver a high-quality, reliable, and user-friendly courier service system application.

Systems Operations and Infrastructure Division of the Philippine Statistics Authority Towards Real-Time Service Delivery

This research explores the revolutionary path taken by the Philippine Statistics Authority’s (PSA) Systems Operations and Infrastructure Division in its pursuit of real-time service delivery. The division deliberately integrates its operations with modern technology breakthroughs in response to the changing demands for data. Clarifying the strategic objectives of the division is the main focus of the study. These include utilizing cutting-edge technologies, infrastructure optimization, and process simplification to provide a smooth and quick flow of statistical data. The division uses methodical approaches, such as technology integration, process automation, and careful data management, which are described in the methodologies section. It offers information on the actions made to bring the division’s operations into line with the main goal of accomplishing real-time service delivery. The division’s initiatives have produced measurable benefits, which are highlighted in the results section. These include increased system reliability, faster data processing, and much lower service delivery latency. The positive impact of the adopted adjustments is substantiated by quantifiable metrics and success indicators. The report concludes by considering the critical role that the Systems Operations and Infrastructure Division has played in moving the industry closer to real-time service delivery. It summarizes lessons learned, identifies obstacles overcome, and looks forward to more developments in the field of information distribution. It is an invaluable resource for businesses and governmental bodies looking to improve service delivery methods through technological changes. The Systems Operations and Infrastructure Division of the PSA provides insights into best practices for navigating the changing information management landscape. Keywords: Information Technology, Public Administration, Real-Time Service Delivery, Systems Operations, Infrastructure Optimization, Technology Integration, Process Automation, Data Management Philippines

Integrating Data Pipelines into Release Pipelines: A Comprehensive Examination

The integration of data pipelines within release pipelines has become essential in contemporary software development to ensure a smooth flow of data, boost operational efficiency, and maintain high standards of software delivery. This paper thoroughly examines the concept, architecture, implementation, and advantages of embedding data pipelines into release pipelines. It also addresses the challenges and best practices to optimize this integration.

Ontology-Based IoT Healthcare Systems (IHS) for Senior Citizens

Rapid incremental growth in population causes the virulence of infectious diseases worldwide. Due to this, health hazards with population growth raise pollution in the air, water, and soil and affect the immunity of individuals. To handle the situation, reliable and easy to reach healthcare services are required. The proliferation of connected technologies along with the Internet of Things (IoT) is providing modern healthcare with extensive care. All-pervading IoT technology gaining a very much attraction nowadays. This paper presents a brief about the E-Health Care System along with its framework. This attempt also presents the ontology approach as data produced by healthcare applications is vast and unstructured which needs to be organized in proper format with a smooth flow of data and also results in less request-response time. Further, this paper discusses the impact of the disease on senior citizens in the current scenario.

Mark Us: A Social Experience Built Using Augmented Reality

MarkUs - a social experience built using the immersive power of Augmented Reality. There has been a plethora of Social Networking Applications around they provide some of the best Social Experiences. However, the territory of Augmented Reality in Social Networking remains an uncharted region. There has been extensive use of face filters by various social networking sites, but we believe that AR has a lot to offer in the social sector. MarkUs tries to extract the best AR experiences for its users by using various technologies which include real-time cloudless atlas and positioning systems. It takes advantage of AR technologies available for mobile phones and makes sure that the heavy computation required for AR does not fall on these devices. MarkUs facilitates various features which include AR journey Books, Various Community Sections dedicated especially to a particular field of interest. AR Live Location Posts and flawless communication with friends. MarkUs uses Mapbox SDK that provides cloudless atlas and positioning required to create Live Location Posts and 3D Map of the world. The proposed system selected React Native to build the foundation. React Native is one of the most popular options to create mobile apps and is extremely lightweight and provides higher flexibility to create flawless UI and their corresponding functionalities. In this system, MongoDB is used to store user data along with their Live Location so that they can reap the benefits of our exclusive features. Also use highly-scalable NodeJs Micro-Services for fast, smooth and efficient data flow.

HTBIDS: Hybrid Trust Based Intrusion Detection System for Physical Layer in WSN

In recent years, wireless sensor network (WSN) is the measure concern over network communication. A number of attacks are occurred at the time of network communication as result it hampers the smooth functionality, data flow and data transmission. In this article, we have proposed a trust-based intrusion detection system for physical layers attacks using DRI and Cross Check method. The HTBIDS is effective method to identify the abnormal nodes in wireless sensor network. The abnormal nodes are attacked by periodic jamming attack. We have considered the periodic jamming attack at physical layer for performance evaluation. Results show that HTBIDS performs better using detection accuracy (DA) and false alarm rate (FAR).

Evolution of optical networks: from legacy networks to next-generation networks

Abstract The requirement for the huge bandwidth-demanding applications has urged researchers to develop improved data pipes that could allow smooth data flow. Revolutionary growth has been witnessed in the domain of the telecommunication industry, which has opened new horizons for connectivity among humans and devices alike especially, in the era of 5G. The advancement from TDM multiplexed signal transmitted over copper wire to the flexible and smart grid along with ethernet passive optical networks or space division multiplexed over optic fiber introducing enormous speed in 100 of Gbps has contributed to the fastest communication. The heterogeneous structure and network complexity require the automating of telecommunication services which have been assisted with the incorporation of machine learning and artificial intelligence, highlighting the new era of communication with the reliability and fastest accessibility. This survey reports the evolution of optical carrier generations and advancement in networks along with the fundamental achievements to comprehend the supportive competition while highlighting the gaps and challenges for future work.

The impact of integrating electronic referral within a musculoskeletal model of care on wait time to receive orthopedic care in Ontario

An MSK model of care for hip and knee patients integrated with an electronic referral solution (eReferral) has been deployed within four subregions across Ontario. Referrals are sent from primary care offices to a central intake (CI), where the referral forms are reviewed and forwarded, if appropriate, to a rapid access clinic (RAC) where patients are assessed by an advanced practice clinician (APC). The pragmatic design of eReferral allows for a seamless flow of electronic orthopedic referrals from primary care to CI. It also enables CI to process and transcribe faxed referrals into the eReferral system for a smooth flow of data electronically to the RACs. In general, wait time is the time interval between receiving the patient’s referral at CI or the surgeon’s office until receiving the orthopedic surgeon's first consultation. Wait time is further broken down into wait 1 a and wait 1 b. Wait 1 a is the time between the receipt of the referral at CI until the date of the first initial assessment at the RAC. This study aimed at: a) assessing the processing time of orthopedic referrals at central intakes (CI) to be forwarded to the RAC, b) assessing the wait time (wait 1 a) of orthopedic referrals processed through the eReferral system to receive an initial assessment at the RACs. c) comparing the ability of the RACs to meet the target wait time for assessment (four weeks) by the method of referral (eReferrals vs. fax). d) evaluating patients’ satisfaction with the length of time they waited to receive care at the RACs with eReferral. We used Ocean eReferral database to access MSK hip and knee referral data processed through the system. Patients whose referrals were initiated electronically through the system and opted to receive email notification of their referral status had the opportunity to take an online satisfaction survey embedded in the booked appointment notification message. There were 1,723 patients initially referred electronically for hip, and knee pain consults, while 13,780 referrals started as paper-based and transcribed into the system to be forwarded later electronically by CI to a RAC. Higher mean processing time at CI by 21.76 days for paper-based referral was detected as opposed to referrals received electronically (p<0.001). RACs took significantly less time to book appointments for referrals initiated electronically with a shorter average wait 1a of 21.42 days for eReferrals compared to paper-based referrals (p<0.001). RACs timeframe to book an appointment was significantly shorter for eReferrals versus fax referrals. A total of 393 patients completed the patient satisfaction survey with a response rate of 16%. Overall, 87.7% were satisfied with their experience with the eReferral process, and 81% agreed that they had waited a reasonable time to receive the needed care. eReferral can elicit faster processing of referrals and shorter wait time for patients, which improved patient satisfaction with the referral process.

CHALLENGES IN OPERATIONS AND MAINTENANCE OF ANTARCTICA GROUND STATION FOR EARTH OBSERVATION SATELLITES

Abstract. Remote sensing and Geographical Information System (GIS) through Earth Observation (EO) Satellites have become most important tools for many of the societal applications of day-to-day life, during the past few decades of the 21st century, and this need is rapidly increasing. Presently, EO payload (PLD) data from Polar Orbiting Indian Remote Sensing (IRS) Satellite Missions is received at the Integrated Multi-mission Ground segment for Earth Observation Satellites (IMGEOS) at NRSC, Hyderabad, India. But at this geographical location, only four out of fourteen orbits data can be acquired from each of the polar satellites. These polar satellite orbits converge at poles, hence establishing a ground station at Polar Regions has an advantage of acquiring data from ten to twelve orbits.To increase the capability, a data reception Ground Station and Communication facility was established by ISRO at Bharati Station, Antarctica, located at 69° South and 76° East, in 2012–2013 (Austral Summer). This station is maintained for flawless operations and smooth flow of IRS Satellites EO data from Antarctica, by three Scientists/Engineers from ISRO, who overwinter at Antarctica, along with other Expedition members, by clearing the pre-requisites for an Antarctica Expedition. While this location is suitable to establish a Ground Station, the local conditions are a challenge to be faced (when established then, and now) to operate and maintain it 24 × 7 throughout the year.

Performance Analysis and Optimization of Distributed Workflows in Heterogeneous Network Environments

Large-scale e-science features complex DAG-structured workflows comprised of computing modules with intricate inter-module dependencies. Mapping such workflows in heterogeneous network environments and optimizing their end-to-end performance are crucial to the success of scientific collaborations that require fast system response and smooth data flow. We construct analytical cost models and formulate workflow mapping as optimization problems for minimum end-to-end delay and maximum frame rate. The difficulty of these problems essentially arises from the topological matching nature in the spatial domain, which is further compounded by the resource sharing complicacy in the temporal dimension. For unitary processing applications, we develop a workflow mapping algorithm based on a recursive critical path optimization procedure to minimize the latency; while for streaming applications, we conduct a rigorous workflow stability analysis and develop a layer-oriented dynamic programming solution based on topological sorting to identify and minimize the global bottleneck time. The accuracy of the proposed exact delay calculation algorithm is verified in comparison with an approximate solution, a dynamic distributed system simulation program, and a real network deployment, and the performance superiority of the proposed mapping approaches are illustrated by extensive simulation-based comparisons with existing algorithms and verified by large-scale experiments on real-life scientific workflows through effective system implementation and deployment in real networks.

P2P cloud network services for IoT based disaster situations information

In order to cope with disaster situations properly, it is very important to identify the disaster scale and provide the accurate information of the site to the appropriate authorities including disaster site and Central Disaster Management Center, on-site command post, etc. and share the information provided. In particular, sharing information on disaster situations should control the disaster quickly to prevent the disaster situation from lasting and expanding. However, in the event of a large-scale disaster, delay is caused in the existing commercial network and therefore, the disaster situation cannot be communicated quickly and accurately. In order to determine the situation exactly in the event of a disaster, safety and connectivity of the network and flow of data are very important. Even if the stability of the network and connection of nodes are resolved in the network of each agency business operator, it is necessary to share the platform between networks for IoT/M2M communication for the smooth flow of data. Recently, the disaster safety net of combining existing disaster standard technology with Ubiquitous Technology and Smart IT such as Tetra of Europe, iDEN of the U.S., etc. has been built for disaster safety communications. In addition, systems useful for demand-centered, site-centered immediate disaster response by using Mobile, SNS, cloud computing, etc. are being built and designed to play an important role in the disaster information system especially through IoT, P2P cloud network, big data, etc. Therefore, in this paper, we proposed the P2P cloud network service for IoT based disaster situations information according to the paradigm of the changing times. The proposed service is to combine IoT/M2M network with P2P cloud service for rapid and smooth response in the event of a disaster and provide the results as social services such as SNS. To this end, the wide area wireless disaster information network system has been built in the local and each local network is connected to each other to provide disaster situations by using the server of the disaster area. At this time, each server was to be interconnected via P2P network and to be connected automatically by software-based network in P2P Cloud System. Also, the cognitive cycle was applied for selecting optimal wireless link and router of P2P Cloud-based Disaster Information Network and the danger situations of the disaster area were to be provided to the user by configuring disaster information component for providing services and building central disaster information platform managing it.

Innovative Technological Approach to Ebola Virus Disease Outbreak Response in Nigeria Using the Open Data Kit and Form Hub Technology.

The recent outbreak of Ebola Virus Disease (EVD) in West Africa has ravaged many lives. Effective containment of this outbreak relies on prompt and effective coordination and communication across various interventions; early detection and response being critical to successful control. The use of information and communications technology (ICT) in active surveillance has proved to be effective but its use in Ebola outbreak response has been limited. Due to the need for timeliness in reporting and communication for early discovery of new EVD cases and promptness in response; it became imperative to empower the response team members with technologies and solutions which would enable smooth and rapid data flow. The Open Data Kit and Form Hub technology were used in combination with the Dashboard technology and ArcGIS mapping for follow up of contacts, identification of cases, case investigation and management and also for strategic planning during the response. A remarkable improvement was recorded in the reporting of daily follow-up of contacts after the deployment of the integrated real time technology. The turnaround time between identification of symptomatic contacts and evacuation to the isolation facility and also for receipt of laboratory results was reduced and informed decisions could be taken by all concerned. Accountability in contact tracing was ensured by the use of a GPS enabled device. The use of innovative technologies in the response of the EVD outbreak in Nigeria contributed significantly to the prompt control of the outbreak and containment of the disease by providing a valuable platform for early warning and guiding early actions.

Distributed Throughput Optimization for Large-Scale Scientific Workflows Under Fault-Tolerance Constraint

With the advent of next-generation scientific applications, the workflow approach that integrates various computing and networking technologies has provided a viable solution to managing and optimizing large-scale distributed data transfer, processing, and analysis. This paper investigates a problem of mapping distributed scientific workflows for maximum throughput in faulty networks where nodes and links are subject to probabilistic failures. We formulate this problem as a bi-objective optimization problem to maximize both throughput and reliability. By adapting and modifying a centralized fault-free workflow mapping scheme, we propose a new mapping algorithm to achieve high throughput for smooth data flow in a distributed manner while satisfying a pre-specified bound of the overall failure rate for a guaranteed level of reliability. The performance superiority of the proposed solution is illustrated by both extensive simulation-based comparisons with existing algorithms and experimental results from a real-life scientific workflow deployed in wide-area networks.

The factors causing failure of foreign enterprises resource planning (ERP) systems in Pakistan

The purpose of this paper is to examine the causes and reasons of failure of foreign enterprises resource planning (ERP) system’s adoption in Pakistan. ERP integrates all the resources (hardware, software, man power, product and process) of an organization and provides a link to each department for smooth flow of data, information, knowledge, resulting in increased productivity and efficient processes. The paper takes on the descriptive research (research design) to explore the factors that lead to failure of ERPs in developing economies focusing on Pakistan. In this study, data was collected through interviews (mixed mode) and questionnaires from ERP providing companies aimed at gathering data on situations where ERP was implemented and failed. The research identified many factors required for the successful implementation of the ERP and many reasons for failure. Although, the research was carried out on a small scale (and can be enhanced), yet it is assumed to set out the parameters for the successful ERP implementation in Pakistan. The research has also shown that the benefits of some areas of ERP are still to be understood by the stakeholders, while the proper need definition from the ERP implementing organization and knowledge of the ERP usage by the top management remains the highest factors of influence towards the failure of foreign ERP systems in Pakistan.

Modeling and simulation of distributed computing workflows in heterogeneous network environments

Next-generation computation- and network-intensive collaborative applications in various science, engineering, and e-commerce fields feature large-scale computing workflows of complex structures. Efficient algorithms are needed for task scheduling, module deployment, and service provisioning to support the execution of such distributed workflows in heterogeneous network environments and optimize their end-to-end performance for fast system response or smooth data flow. However, deploying large-scale distributed applications in real network environments is extremely challenging due to the inherent dynamics in the reliability, availability, accessibility, and capacity of massively distributed system resources, which are typically shared among a broad community of users over the Internet or dedicated connections. We propose a simulation system to study the execution dynamics of distributed computing workflows and evaluate the network performance of workflow scheduling or mapping algorithms before actual deployment and experimentation. The proposed simulation system visually illustrates the dynamic execution process of workflows in network environments by simulating module execution on computer nodes and data transfer over network links in a completely distributed and parallel manner. Furthermore, the simulation system takes background traffic and workload into consideration to achieve a high level of simulation accuracy for distributed applications deployed in shared production network environments. We implement the simulation system using multi-threaded programming and conduct extensive testings on various mapping schemes using a large number of simulated workflows and networks. The simulation-based performance measurements are quantitatively confirmed by both the experimental observations collected in real networks and the theoretical results obtained by rigorous performance analysis based on well-defined mathematical models.

Highly Flexible Row and Column Redundancy and Cycle Time Adaptive Read Data Path for Double Data Rate Synchronous Memories

This paper describes two circuit techniques useful for the design of high density and high speed low cost double data rate memories. One is a highly flexible row and column redundancy circuit which allows the division of flexible row redundancy unit into multiple column redundancy unit for higher flexibility, with a new test mode circuit which enables the use of the finer pitch laser fuse. Another is a compact read data path which allows thp smooth data flow without wait time in the high frequency operation with less area penalty. These circuit techniques achieved the compact chip size with the cell efficiency of 60.6% and the high bandwidth of 400MHz operation with CL=2.5.

Two-way TCP traffic over rate controlled channels: effects and analysis

We study the performance of bidirectional TCP/IP connections over a network that uses rate-based flow and congestion control. An example of such a network is an asynchronous transfer mode (ATM) network using the available bit rate (ABR) service. The sharing of a common buffer by TCP packets and acknowledgment (acks) has been known to result in an effect called ack compression, where acks of a connection arrive at the source bunched together, resulting in unfairness and degraded throughput. It has been the expectation that maintaining a smooth flow of data using rate-based flow control would mitigate, if not eliminate, the various forms of burstiness experienced with the TCP window flow control. However, we show that the problem of TCP ack compression appears even while operating over a rate-controlled channel. The degradation in throughput due to bidirectional traffic can be significant. For example, even in the simple case of symmetrical connections with adequate window sizes, the throughput of each connection is only 66.67% of that under one-way traffic. By analyzing the periodic bursty behavior of the source IP queue, we derive estimates for the maximum queue size and arrive at a simple predictor for the degraded throughput, for relatively general situations. We validate our analysis using simulation on an ATM network using the explicit rate option of the ABR service. The analysis predicts the behavior of the queue and the throughput degradation in simple configurations and in more general situations.