Tracking Services Research Articles

Comprehensive Tracer Study of San Sebastian College-Recoletos Manila (2018-2023)

The employability of graduates from San Sebastian College Recoletos (SSCR) between 2018 and 2023 is under scrutiny in the Comprehensive Tracer Study, which also delves into the impact of their education on their ability to thrive in the realm. This research aims to analyze the employment status and demographic characteristics of these graduates, evaluate their perspectives on job-hunting practices, and assess how effectively their education equipped them for the working world. A total of 440 graduates participated in a research project by completing a self-designed survey tool via a platform. In order to uncover patterns and connections within the data set, we carried out an analysis utilizing weighted calculations alongside examining the frequency distributions and conducting an Analysis of Variance (ANOVA). The outcomes indicate that most graduates achieve job placements, with a proportion securing positions shortly following graduation. The research underscores the importance of workshops and conferences in enhancing job prospects, particularly for individuals who land jobs within a year post-graduation. Considering everything, the research showcases the effectiveness of SSCR initiatives in facilitating graduates’ transition into the job market and identifies areas where enhanced graduate tracking and support services are needed. This analysis could assist SSCR in enhancing its strategies for equipping students with the skills, for employment success.

Online and offline delivery qualities: O2O satisfaction and loyalty through technology acceptance model

This study presents an in-depth examination of customer satisfaction dynamics within the rapidly growing O2O food delivery (OFD) sector. Recognizing the exponential market growth and the gradual rise in consumer complaints, we seek to address the gaps in current academic research that tends to overlook the distinction between online and offline service experiences, as well as the psychological foundations of technology adoption. We propose a series of hypotheses grounded in a comprehensive theoretical framework that distinguishes between online and offline dimensions of consumer satisfaction and explores their interrelation by incorporating the technology acceptance model (TAM). We posit that, regarding online satisfaction, the quality of food information, the quality delivery tracking service, and user privacy protection functions from OFD applications hold positive significance for online customer satisfaction. Additionally, considering offline satisfaction, we assert that delivery quality and environment of the delivery service (i.e., delivery scape) contribute positively to offline customer satisfaction. We adopt trust transfer theory to hypothesize a positive relationship between online and offline satisfaction to comprehend a continuous flow in how consumer satisfaction develops. The paper also examines the pathway by which online satisfaction influences consumer loyalty through TAM. By investigating the dynamics regarding these relationships, this study contributes to offering valuable insights that could enhance OFD users’ satisfaction and their loyalty.

PrivateGaze: Preserving User Privacy in Black-box Mobile Gaze Tracking Services

Eye gaze contains rich information about human attention and cognitive processes. This capability makes the underlying technology, known as gaze tracking, a critical enabler for many ubiquitous applications and has triggered the development of easy-to-use gaze estimation services. Indeed, by utilizing the ubiquitous cameras on tablets and smartphones, users can readily access many gaze estimation services. In using these services, users must provide their full-face images to the gaze estimator, which is often a black box. This poses significant privacy threats to the users, especially when a malicious service provider gathers a large collection of face images to classify sensitive user attributes. In this work, we present PrivateGaze, the first approach that can effectively preserve users' privacy in black-box gaze tracking services without compromising gaze estimation performance. Specifically, we proposed a novel framework to train a privacy preserver that converts full-face images into obfuscated counterparts, which are effective for gaze estimation while containing no privacy information. Evaluation on four datasets shows that the obfuscated image can protect users' private information, such as identity and gender, against unauthorized attribute classification. Meanwhile, when used directly by the black-box gaze estimator as inputs, the obfuscated images lead to comparable tracking performance to the conventional, unprotected full-face images.

Acceptance of IoT-based E-coin Track-and-trace: A Case of the Digital Euro Project in Italy

As the world becomes increasingly digitalised, there are growing concerns about the use of big data and machine learning techniquesto monitor and control citizens’ spending habits. This is particularly the case regarding Central Bank Digital Currencies (CBDC), whichare being trialled by an increasing number of countries. There is a perception that such currencies could violate privacy due to thecentralisation of money liability. The aim of this research is to assess whether a universal e-coin level tracking service of money and public expenditures, available to everyone and inspired by Internet of Things (IoT) architectures and standards, could instil trust ininstitutions while increasing the acceptance of CDBCs. The research methodology comprises three key elements: (i) the conceptualisation and implementation of an IoT-based CBDC, (ii) a qualitative, technical and compliance assessment with regard to the specific reference to the Digital Euro (D€) project, and (iii) a survey we conducted among 351 respondents to ascertain the potential for CBDC acceptance within Italy. The results demonstrate that the prototype is a viable concept despite storage limitations. Furthermore, 73.83 percent of respondents who initially expressed scepticism indicated that they would be more inclined to adopt the CDBC instrument if a universal track-and-trace tool of money were made available.

Blockchain Technology for tracking and tracing containers: model and conception

The maritime industry has increasingly integrated advanced technologies such as AI, Blockchain, Big Data, and IoT, transforming traditional port operations into smart facilities aimed at enhancing global trade competitiveness. A particular focus has been on improving tracking and tracing services, with Blockchain technology emerging as pivotal for ensuring data integrity, transparency, and traceability across supply chains. This article proposes a blockchain-based tracking and tracing system model tailored for monitoring containers in Moroccan ports. Utilizing the Unified Modeling Language (UML), the model seeks to optimize resource allocation and boost stakeholder satisfaction through detailed diagrams and functional data requirements depiction. Despite challenges such as IoT terminal platform connectivity and operator resitance, successful implementation was achieved, establishing a foundational framework for a comprehensive container monitoring system. This model provides valuable insights for supply chain professionals and scholars interested in item tracking, aiming to integrate Blockchain with technologies like RFID, GPS, RTLS, QR Codes, BLE, and IoT sensors to enhance port operation efficiency and container management effectiveness. By leveraging these integrated technologies, ports can further improve operational efficiency and ensure accurate traceability of containers throughout the supply chain, contributing to overall trade facilitation and economic growth..

Qatar's multifaceted humanitarian role in Afghanistan since August 2021

AbstractMotivationQatar's humanitarian role in Afghanistan, a less‐explored example of a non‐traditional actor, is crucial in understanding international responses to geopolitical crises. Examining Qatar's involvement provides insights into the complex dynamics of humanitarian assistance, diplomatic efforts, and post‐crisis challenges.PurposeThe study examines Qatar's multifaceted role in Afghanistan since 2021, highlighting its impact as a non‐traditional actor in complex humanitarian operations and diplomacy.Approach and methodsThe research combines a desk review of online sources, academic literature, reports, non‐governmental organization documents, and media articles with first‐hand observations and informal stakeholder interviews. It also analyses international aid statistics from the United Nations Office for the Coordination of Humanitarian Affairs' Financial Tracking Service and the Organisation for Economic Co‐operation and Development's Development Assistance Committee.FindingsQatar emerged as a key humanitarian player in Afghanistan, adopting a whole‐of‐society approach. Its efforts encompassed emergency relief, evacuations, educational support, and humanitarian diplomacy, effectively bridging the Taliban with international actors after the takeover.Policy implicationsThis research highlights the impactful role of non‐traditional donors, as seen with Qatar in Afghanistan, emphasizing their potential in complex humanitarian scenarios. The study advocates recognizing and leveraging the unique capabilities of smaller states and non‐traditional actors in humanitarian responses, promoting capacity building to harness their institutional agility and societal resources effectively.

WOMEN SAFETY APP

The Women Safety App operates on a multifaceted approach, incorporating real-time assistance, precise location tracking, and immediate access to emergency services. By capitalizing on the ubiquity of smartphones, this project strives to provide a swift and effective response to potential threats that women may encounter in various situations. The core features of the app include a panic button for instant distress signals, live location sharing to facilitate timely assistance, and a streamlined communication channel with emergency services. These elements collectively contribute to fostering a safer environment for women, instilling a sense of confidence and security as they navigate their daily lives. The Women Safety App project addresses the critical issue of women's safety by leveraging technology to provide a reliable and accessible solution. In today's society, incidents of gender-based violence, harassment, and discrimination underscore the urgent need for effective measures to protect women's well-being and security. Existing safety mechanisms often fall short, relying on manual interventions and traditional communication channels that may not provide immediate assistance during emergencies. The Women Safety App aims to bridge this gap by offering real-time assistance, location tracking, and emergency services through a mobile application. Its key advantage lies in delivering instant distress signals, enabling quick alerts to trusted contacts and emergency responders in threatening situations. Additionally, live location tracking allows users to share their whereabouts for added safety.

Valuing Modern Technologies to Boost the Circular Economy in the Fashion Industry

Abstract In the context of solving pollution problems, the circular economy appears to be a mandatory practice because it emphasises the principle of reuse - repair - reconditioning - recycle. In this context, the paper aims to analyse how modern technologies facilitate the implementation of circular economy principles through better traceability of goods produced and used in the fashion industry. In this way, our research is exploratory and the information on which it is based was gathered using the Google search tool, which identified brands who use Big Data, RFID and QR code tools, as well as online tools (cloud-based platforms) that offer integrated garment tracking services. Following detailed analysis of EU data, it was found that major companies have integrated QR Code technology into their products and cloud-based platforms are increasingly used.

A Mobile Application Based Optimized Out-Patient Emergency Request Model

This paper developed a mobile APP called Health Emergency Request APP (HER-APP). The App sends out-patients‘ emergency request to any closest health personnel within a particular location and matches a patient to a particular health personnel for immediate attention. We observed that the process of responding to out-of-hospital emergencies after a crisis have faced a lot of communication challenges between patients and the nearest healthcare personnel especially in Nigeria. There is also a problem of assigning a patient to the most qualified health personal for better care. This has resulted in increased mortality even when such emergency could better be handled. It becomes compelling to develop a mobile APP that allows a seamless communication between patient under emergency and the nearest medical expert with medical facility to save lives prior to the full engagement of the attention of a medical doctor or ambulance. This emergency request service-oriented mobile application helps patients contact any closest health personnel within a particular location using a location tracking service. The mobile application implements a matching algorithm between patients and responders, and assists people in emergency to get quick pre-clinical treatment. It uses an optimized service-oriented architecture which reduces the communication process between a patient in an emergency and the doctor or responder using a Google global positioning system as a location tracking service to helps track a patient requesting for assistance as well as all available responders. The APP uses location factor to determine a model to enhance the system on a large scale basis to provide a dispatch method to allocate patients to responders. This paper enhanced the Hungarian model and determines the best patient-responder match. The mobile APP is available at www.github.com/magnifikuc.

Geopolitical risk and the national logistics performance

ABSTRACT Using a panel of 43 countries over the period 2007–2022, we provide evidence of the negative effects of geopolitical risk on national logistics performance. Digging deeper into the main dimensions of the national logistics performance, we find that elevated geopolitical risk deteriorates the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, international shipment pricing, the competence and quality of logistics services, tracking and tracing services, and the timeliness of delivery services.

An Up-View Visual-Based Indoor Positioning Method via Deep Learning

Indoor positioning plays a crucial role in various domains. It is employed in various applications, such as navigation, asset tracking, and location-based services (LBS), in Global Navigation Satellite System (GNSS) denied or degraded areas. The visual-based positioning technique is a promising solution for high-accuracy indoor positioning. However, most visual positioning research uses the side-view perspective, which is susceptible to interferences and may cause concerns about privacy and public security. Therefore, this paper innovatively proposes an up-view visual-based indoor positioning algorithm. It uses the up-view images to realize indoor positioning. Firstly, we utilize a well-trained YOLO V7 model to realize landmark detection and gross extraction. Then, we use edge detection operators to realize the precision landmark extraction, obtaining the landmark pixel size. The target position is calculated based on the landmark detection and extraction results and the pre-labeled landmark sequence via the Similar Triangle Principle. Additionally, we also propose an inertial navigation system (INS)-based landmark matching method to match the landmark within an up-view image with a landmark in the pre-labeled landmark sequence. This is necessary for kinematic indoor positioning. Finally, we conduct static and kinematic experiments to verify the feasibility and performance of the up-view-based indoor positioning method. The results demonstrate that the up-view visual-based positioning is prospective and worthy of research.

Angkut.in: The Future of Trucking by Digital Product Design Journey

Jepara Regency in Central Java, Indonesia, is renowned as the "World Carving Center" due to its flourishing furniture carving industry. Despite successfully exporting carvings globally, the distribution process encounters challenges with conventional methods, primarily due to a limited truck fleet exacerbated by the post-pandemic situation. This study aims to scrutinize the effectiveness of "Angkut.in" as an innovative solution for overcoming hurdles in heavy goods distribution, particularly furniture. Utilizing Design Thinking, the research incorporates an analysis of the application of the Technology Acceptance Model (TAM) and digital marketing strategies within the "Angkut.in" application design. Employing a Supply Chain Management (SCM) approach, the research assesses the application's impact on local innovation growth, operational efficiency, and the competitiveness of the furniture industry. Market analysis indicates a focus on the online furniture entrepreneur segment. The marketing strategy involves real-time tracking services, live price checking, and user-friendly application interfaces. The business model adopts a Business-to-Business (B2B) approach, emphasizing transportation services for large goods businesses. The business identity design encompasses color selection, typography, and graphic elements that mirror the innovative and reliable nature of goods delivery services. Risk analysis covers technological factors, market competition, loss of goods, data security, capital limitations, regulatory changes, market acceptance, and force majeure. Angkut.In is categorized as a low-risk business according to the risk analysis matrix. The prototype validation by UKM Partners yielded a score of 8.5 out of 10, indicating maturity and compliance with most evaluation criteria. The provided fix notes will guide further development steps before the official launch.

Characterization of Change in Tree Cover State and Condition over the Conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Analysis of Implementation Strategies for Innovative Library Services in the Construction of First-class Disciplines in Universities

University library plays a crucial role in the construction of first-class disciplines. This study aims to explore how library can innovate their services to promote the construction of first-class disciplines. By combining literature review and empirical analysis, this research analyzes relevant information and user situations in first-class disciplines, and proposes new initiatives for the construction of literature and information resources in universities. Measures such as optimizing the library's collection structure, highlighting the collection characteristics of first-class discipline literature, focusing on the construction of digital information resources for first-class disciplines, and rational allocation of journal resources can meet the literature needs of first-class disciplines better. Additionally, establishing a navigation database for first-class disciplines, implementing subject librarians, conducting in-depth information development and project tracking services, integrating web search engines, providing online consultation services, and building a repository of expert papers for first-class disciplines as innovative service functions can effectively promote the construction of first-class disciplines. The results of this study have significant implications for the role positioning and service innovation of university library in the construction of first-class disciplines.

Post-Purchase Experience in Online Shopping and Their Impact on Customer Satisfaction at Blibli.Com

This study aims to determine the effect of Post-Purchase Experience on Customer Satisfaction and Future Purchase Intention on the use of the Blibli.com application in Surabaya. This research method uses an online survey of 200 respondents in Surabaya who have used the Blibli.com application, especially those who have used the return facility. The collected data were analyzed using the Structural Equation Modeling (SEM) measurement model assisted by using SPSS Version 24.0 and AMOS Version 23.0 applications. The results of this study found that several variables in the Post-Purchase Experience, namely the Shipping Service and Tracking Service variables were not supported on Customer Satisfaction on the use of the Blibli.com application in Surabaya. Other variables, namely Return service and Customer Service have an effect on Customer Satisfaction, and Customer Satisfaction has an effect on Future Purchase Intention.

Radar observation and recontruction of Cosmos 1408 fragmentation

The population of objects in space has increased dramatically over recent decades. Space debris now represents the majority of objects in space resulting from inactive satellites, breakups, collisions and fragmentations. It has become a concern for institutions all over the world and, as such, it has led to the fostering of several programmes to counter the issues. Among these, the use of ground-based sensors for Space Surveillance Tracking (SST) activities and services and tools for analysing fragmentations play a crucial role.This work presents the activities carried out by Politecnico di Milano, Italian Space Agency and Italian National Institute of Astrophysics in this framework, using data from SST networks and the observation measurements from Bistatic Radar for LEo Survey (BIRALES), an Italian bistatic radar belonging to the EUropean Space Surveillance and Tracking (EUSST), which contributed most to the monitoring of the cloud of fragments. Exploiting Two-Line Elements (TLEs) of observed fragments, a reverse engineering approach is used to reconstruct a fragmentation in orbit through the use of the software suite PUZZLE developed at Politecnico di Milano. The analyses focus on studying the fragmentation of the Cosmos 1408 satellite, which occurred on November 15th 2021 following an Anti-SATellite (ASAT) missile test. More than 1000 trackable pieces and millions of smaller debris (estimated from numerical analysis) were produced by this event, increasing the population of inactive objects around the Earth, and threatening nearby orbiting objects.First, the processing method adopted from BIRALES in observing Cosmos debris is presented and discussed and a critical analysis about the derivable information is conducted. Then, these data and those from SST network observations are used to identify the epoch and the location of the fragmentation. In this procedure, the software toolkit PUZZLE, developed by Politecnico di Milano within a project funded by the Italian Space Agency and extended through the European Research Council, is used.

Willingness to pay for antiretroviral therapy, viral load, and premium services; A contingent valuation survey of people living with HIV in southern Nigeria.

With stagnating funding for HIV and AIDS control programs in Nigeria, alternative funding models for antiretroviral therapy (ART) including out of pocket payment are being considered to sustain momentum epidemic control targets. We assessed willingness to pay for ART related services, and factors associated with willingness to pay. Between July and August 2019, we conducted a survey among people living with HIV (PLHIV) on ART in 3 states in southern Nigeria. Randomly sampled respondents on ART for at least 6 months, aged ≥ 18 years, able to communicate in English or pidgin English, and consenting to the survey were enrolled. Respondents were asked if they were willing to pay for clinical consultation, antiretroviral drugs (ARVs), viral load testing services and premium ART services (including fast track services). Respondents indicating willingness to pay for any of these services were asked the maximum amount they were willing to pay using contingent valuation methodology. We assessed the weighted proportions of PLHIV on ART willing to pay for ART and used survey-featured logistic regression measures to assess sociodemographic and ART related factors associated with willingness to pay for ART services. Overall, 1,598 PLHIV with a mean age of 39.03 years (standard deviation [SD]: 11.23 years), were included in this analysis. Of these, 65.8% (1,079), 73.9% (1,192), 61.0% (995) and 33.6% (472) were willing to pay for ART consultation, ARVs, viral load testing services and premium ART services respectively. The median maximum amount PLHIV were willing to pay for clinical consultation and for ARVs was NGN1,000 (USD equivalent of $2.78; interquartile range [IQR]: 500-2,000) respectively, and NGN2,500 (USD equivalent of $6.94; IQR: NGN1,000-5,000) and NGN2,000 (USD equivalent of $5.56; IQR: NGN1,000-3,000) for viral load testing and premium ART services respectively. Receiving ART in Lagos state, being employed and having a monthly income of NGN100,000 or more was associated with willingness to pay for the various ART services. We found generally high-level of willingness to pay for ART consultation, ARVs and viral load testing services but low willingness to pay for premium ART services among PLHIV on ART. The maximum amount PLHIV were willing to pay for various ART services fell short of benchmarks for alternative funding but can potentially supplement ART by funding differentiated service delivery models that require nominal amounts to facilitate person-centered differentiated service delivery models.

Angle-Based SLAM on 5G mmWave Systems: Design, Implementation, and Measurement

Simultaneous localization and mapping (SLAM) is a key technology that provides user equipment (UE) tracking and environment mapping services, enabling the deep integration of sensing and communication. The millimeter-wave (mmWave) communication, with its larger bandwidths and antenna arrays, inherently facilitates more accurate delay and angle measurements than sub-6 GHz communication, thereby providing opportunities for SLAM. However, none of the existing works have realized the SLAM function under the 5G New Radio (NR) standard due to specification and hardware constraints. In this study, we investigate how 5G mmWave communication systems can achieve situational awareness without changing the transceiver architecture and 5G NR standard. We implement 28 GHz mmWave transceivers that deploy OFDM-based 5G NR waveform with 160 MHz channel bandwidth, and we realize beam management following the 5G NR. Furthermore, we develop an efficient successive cancellation-based angle extraction approach to obtain angles of arrival and departure from the reference signal received power measurements. On the basis of angle measurements, we propose an angle-only SLAM algorithm to track UE and map features in the radio environment. Thorough experiments and ray tracing-based computer simulations verify that the proposed angle-based SLAM can achieve sub-meter level localization and mapping accuracy with a single base station and without the requirement of strict time synchronization. Our experiments also reveal many propagation properties critical to the success of SLAM in 5G mmWave communication systems.

A survey of indoor positioning systems based on a six-layer model

Indoor positioning has attracted considerable interest in both the industry and academic communities because of its wide range of applications, such as asset tracking, healthcare and context-aware services like targeted advertisements. While there are many indoor localisation methods, each has its advantages and disadvantages, taking into consideration various factors such as the effect of the indoor environment, ease of implementation, computational cost, positioning accuracy, etc. In other words, no single solution can cater for all different situations. Although many survey papers have been published on indoor positioning, new techniques and methods are proposed every year, so it is important to stay abreast of its latest developments. In addition, each survey has its own classification for indoor positioning systems without a common scheme. Inspired by the well-known OSI model and TCP/IP model, it would be desirable to develop a systematic framework for studying indoor positioning systems. In this paper, we make this new contribution by introducing a systemic survey framework based on a six-layer model to give a comprehensive survey of indoor positioning systems, namely: device layer, communication layer, network layer, data layer, method layer and application layer. Complementing the previous survey papers, this paper provides a survey of the latest research works on indoor positioning based on the six-layer model. Our emphasis is on systematic categorisation, machine learning-based enhancements, collaborative localisation and COVID-19-related applications. The six-layer model should provide a useful framework and new insights for the research community.

Retracted: Research on the Architecture of Cold Chain Logistics Multimedia Monitoring and Tracking Service Platform Based on Fuzzy Sorting and Heuristic Algorithm

Retracted: Research on the Architecture of Cold Chain Logistics Multimedia Monitoring and Tracking Service Platform Based on Fuzzy Sorting and Heuristic Algorithm