Tracking Services Research Articles

Post-conflict development, reviewing the water sector in Somalia

Somali post-conflict development faces many challenges that affect the sustainability of the water sector. This paper reviews and analyses the post-conflict development activities in the water sector through local communications and reviewing published materials and databases from international players in Somalia, funding agencies and financial tracking service. The paper has shown that there has been great attention and support given to the country during its post-conflict development. However, most of these initiatives and projects have focused on emerging issues such as tackling food security and water, sanitation and hygiene services. The paper also shows that the continuous funding of emerging issues in Somalia has reduced its long-term sustainability of the water sector and limited its national and long-term benefits but has increased corruption due to increase the gap between actors and local people. Therefore, new transparent cooperative initiatives are needed based on transparent involvement and coordination among donors, local authorities and implementers to improve and develop the water sector and the livelihood in Somalia through a solid water governance system.

Review and Simulation of Counter-UAS Sensors for Unmanned Traffic Management.

Noncollaborative surveillance of airborne UAS (Unmanned Aerial System) is a key enabler to the safe integration of UAS within a UTM (Unmanned Traffic Management) ecosystem. Thus, a wide variety of new sensors (known as Counter-UAS sensors) are being developed to provide real-time UAS tracking, ranging from radar, RF analysis and image-based detection to even sound-based sensors. This paper aims to discuss the current state-of-the art technology in this wide variety of sensors (both academically and commercially) and to propose a set of simulation models for them. Thus, the review is focused on identifying the key parameters and processes that allow modeling their performance and operation, which reflect the variety of measurement processes. The resulting simulation models are designed to help evaluate how sensors’ performances affect UTM systems, and specifically the implications in their tracking and tactical services (i.e., tactical conflicts with uncontrolled drones). The simulation models cover probabilistic detection (i.e., false alarms and probability of detection) and measurement errors, considering equipment installation (i.e., monostatic vs. multistatic configurations, passive sensing, etc.). The models were integrated in a UTM simulation platform and simulation results are included in the paper for active radars, passive radars, and acoustic sensors.

Implementasi Metode Sequential Searching pada Aplikasi “RUMAH KUCING PASIFIK” Berbasis Mobile

Cats are one of the pet mammals, but the difficulty of finding information in caring for and finding a cat is a priority problem for adopters or potential adopters. Therefore, it needs an application that contains a cat search feature to enclose information on caring for a given pet cat “rumah kucing pasifik” in an application.“rumah kucing pasifik” application implemented the sequential searching algorithm as a process of searching for cat data based on location data as search keywords. Software development used the prototype method which included designing a modelling system using the unified model language, interface design, coding and testing using the java programming language and using the firebase database.This application eased to find independent cats for adoption and cat tracking services. The system built still had many shortcomings. Therefore, it still needed improvement and development for further research, such as adding keywords based on cat gender and cat breed.Keywords: Search, Cat Animal

Vehicle Routing Optimization System with Smart Geopositioning Updates

Solving the vehicle routing problem (VRP) is one of the best-known optimization issues in the TLS (transport, logistic, spedition) branch market. Various variants of the VRP problem have been presented and discussed in the literature for many years. In most cases, batch versions of the problem are considered, wherein the complete data, including customers’ geographical distribution, is well known. In real-life situations, the data change dynamically, which influences the decisions made by optimization systems. The article focuses on the aspect of geopositioning updates and their impact on the effectiveness of optimization algorithms. Such updates affect the distance matrix, one of the critical datasets used to optimize the VRP problem. A demonstration version of the optimization system was developed, wherein updates are carried out in integration with both open source routing machine and GPS tracking services. In the case of a dynamically changing list of destinations, continuous and effective updates are required. Firstly, temporary values of the distance matrix based on the correction of the quasi-Euclidean distance were generated. Next, the impact of update progress on the proposed optimization algorithms was investigated. The simulation results were compared with the results obtained “manually” by experienced planners. It was found that the upload level of the distance matrix influences the optimization effectiveness in a non-deterministic way. It was concluded that updating data should start from the smallest values in the distance matrix.

Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990–2050

SummaryBackgroundThe rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020.MethodsWe estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050.FindingsIn 2019, health spending globally reached $8·8 trillion (95% uncertainty interval [UI] 8·7–8·8) or $1132 (1119–1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40·4 billion (0·5%, 95% UI 0·5–0·5) was development assistance for health provided to low-income and middle-income countries, which made up 24·6% (UI 24·0–25·1) of total spending in low-income countries. We estimate that $54·8 billion in development assistance for health was disbursed in 2020. Of this, $13·7 billion was targeted toward the COVID-19 health response. $12·3 billion was newly committed and $1·4 billion was repurposed from existing health projects. $3·1 billion (22·4%) of the funds focused on country-level coordination and $2·4 billion (17·9%) was for supply chain and logistics. Only $714·4 million (7·7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34·3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448–1591) per person in 2050, although spending across countries is expected to remain varied.InterpretationGlobal health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all.FundingBill & Melinda Gates Foundation.

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

With the continuous development of social economy, the logistics system has been continuously improved. In addition to traditional domestic postal transportation and car consignment, emerging logistics methods such as SF Express and Yunda have also emerged. Aiming at the features such as fragility of fruits and vegetables and high storage requirements, in this paper, a cold chain logistics multimedia monitoring and tracking service platform is built in an attempt to monitor the preservation environment and safety status of agricultural products relying on fuzzy sorting and heuristic algorithms, trace agricultural products with labels, and design the direction of the key data. The practice results show that the system is effective.

Emotion and Virality of Food Safety Risk Communication Messages on Social Media

This study investigates how the emotional tone of food safety risk communication messages predicts message virality on social media. Through a professional Internet content tracking service, we gathered news articles written about the 2018 romaine lettuce recall published online between October 30th and November 29th, 2018. We retrieved the number of times each article was shared on Twitter and Pinterest, and the number of engagements (shares, likes, and comments) for each article on Facebook and Reddit. We randomly selected 10% of the articles (n = 377) and characterized the emotional tone of each article using machine learning, including emotional characteristics such as discrete emotions, emotional valence, arousal, and dominance. Conveying negative valence, low arousal, and high dominance, as well as anger and sadness emotions were associated with greater virality of articles on social media. Implications of these findings for risk communication in the age of social media are discussed.

Elderly Fall Detection Devices Using Multiple AIoT Biomedical Sensors

Abstract Due to the influence of degeneration and chronic diseases of elderly people, a higher chance of fall-related injuries occurs among them. Falling is one of the accidents frequently confronted by elderly people, so this issue is worthy of concern. We propose diverse models to analyze falls through a wearable device. Then, we use Artificial Intelligence of Things (AIoT) biomedical sensors for fall detection to build a system for monitoring elderly people’s falls caused by dementia. The system can meet the safety needs of elderly people by providing communication, position tracking, fall detection, and pre-warning services. This device can be worn on the waist of an elderly people. Moreover, the device can monitor whether or not the person is walking normally, transmit the information to the rear-end system, and inform his/her family member via a cellphone app while an accident is occurring. Considering the risks on the fall test of elderly people, this study adopts activities of daily living (ADL) to verify the test. According to the test results, the accuracy of fall detection is 93.7%, the false positive rate is 6.2%, and the false negative rate is 6.5%. To improve the accuracy of fall detection and the timely handling of appropriate referrals, may be highly expected to reduce the occurrence of fall-related injuries. JEL classification numbers: D61, I30, O32. Keywords: Fall Detection, AIoT Sensor, Elderly People.

Feasibility of using a software‐defined baseband for multiple space per aperture (MSPA) ground operations

SummaryThis paper presents the feasibility of performing multiple spacecraft per aperture (MSPA) ground operations by using a low‐cost software‐defined baseband (SDB). The SDB is a Consultative Committee for Space Data Systems (CCSDS)‐compliant baseband that employs a personal computer for signal processing and a low‐cost commercial‐off‐the‐shelf RF front end for RF signal sampling. The SDB is customized to offer traditional telemetry, tracking, and command (TT&C) services for near‐Earth missions operating in S band. The study starts by reviewing MSPA methods already studied by space agencies such as NASA and ESA before going to MSPA methods proposed in the latest CCSDS blue book on RF and modulation systems. The feasibility of operating the CCSDS‐proposed multiple uplink carrier MSPA method using the SDB is assessed after evaluating in‐band interference and out‐of‐band emissions from the uplink signals radiated by the low‐cost RF front end employed by the SDB. Furthermore, we present a case study where the SDB is used in MSPA operations on a typical solid‐state amplifier (SSPA) amplifier typically used in near‐Earth missions.

Deficient DNA mismatch repair and persistence of SARS-CoV-2 RNA shedding: a case report of hereditary nonpolyposis colorectal cancer with COVID-19 infection

BackgroundSeveral independent risk factors have been reported to influence viral shedding following COVID-19 infection, but the influence of host-related molecular factors has not yet been described. We report a case of a cancer patient with Lynch syndrome (hereditary nonpolyposis colorectal cancer, HNPCC) who manifested SARS-CoV-2 PCR (polymerase chain reaction) positivity for at least 54 days after contracting mild COVID-19 illness. We propose that deficient mismatch repair (MMR) may play a role in the prolonged SARS-CoV-2 RNA shedding.Case presentationA patient with Lynch syndrome was under surveillance for metastatic adenocarcinoma after completing palliative chemotherapy in October 2019. Between the period of April 2020 to June 2020, he was admitted multiple times to address several clinical needs mainly related to his underlying malignancy. These included progressive disease observed in the aortocaval lymph nodes leading to recurrent episodes of upper gastrointestinal bleeding, dehydration resulting in acute kidney injury and a short-lived episode of pyrexia. A SARS-CoV-2 PCR of the nasopharyngeal swab (NPS) was positive at his initial admission with mild COVID-19 symptoms. He remained positive on subsequent admissions when tested routinely for SARS-CoV-2 without demonstrating any apparent clinical features of COVID-19 infection.The MMR pathway, a component of DNA damage response (DDR), is impaired in Lynch syndrome due to an inherited genetic mutation. This pathway is also required for viral clearance from the host cells following certain RNA viral infections like influenza virus and other coronaviridae. Here we provide a current understanding of the importance of DDR deficiencies in the clearance of RNA virus and suggest how this may play a similar role in the clearance of COVID-19, as evident in our case that demonstrated persistent positivity.ConclusionThe importance of understanding the scientific basis of extended viral shedding during the COVID-19 pandemic is now centre-stage in the establishment of robust track and trace services to allow the recovery and function of societies and economies. This patient with Lynch syndrome recovered from infection but had prolonged viral positivity, which might merit further investigation to better understand the effect of this condition on infection duration and outcome.

Challenges of Applying AI in Healthcare in India

With the advent of digitalization, upcoming technologies like Artificial Intelligence (AI) are being utilized by healthcare services to manage various healthcare services to mimic human cognitive functions. This technology is expected to bring about a massive change in healthcare. Patient management, clinical decision support, patient tracking, and health care services are the four main AI-enabled fields of the healthcare industry. The method carrying out the study was based on secondary research by the themes of the studies performed earlier using Artificial intelligence in healthcare sector, through observations, interviews and valid documentations from prominent databases, by means of challenges and its analysis and the last by the issues associated with the study and the target groups are the front line workers in healthcare sectors. The AI applications in health care have gathered much attention, but AI's adoption issues have not been significantly tended. There are several challenges of its implementation, such as resolving the unequal relationship between trained physicians and patients and increasing physicians' efficiency to be more effective in their work; providing AI-enabled healthcare equipment in rural communities; and educating physicians or doctors in handling it. AI technologies have the potential to enhance patient outcomes. Still, they may also pose significant risks in terms of inadequate patient risk assessment, medical error, and suggestions for treatment, privacy violations, and others.

The Use Behavior of Tracking and Tracing Services in E-Commerce Logistics

An increasing business transaction can cause rapid growth in online shops and marketplace. One of the affected is an online shop. From several logistic services, tracking and tracing information services are the main focus in this study because online shops as the business partner have a lack of attention in these services. The objective of this study is to investigate the factors of online shop behavior in using tracking and tracing information services.This study used a unified theory of acceptance and use of technology (UTAUT) as the framework. The quantitative data were collected through questionnaires from 207 samples of online shops selling women’s fashion and listed in the marketplace. Data were analyzed using structural equation modeling (SEM) with LISREL 8.70.The result of this study found that “the intention to use” the tracking and tracing information services depend on the effort expectancy (EE) dan social influence (SI), while “user behavior” depends on facilitating condition (FC) and the intention to use. The ease of access factor and learning the tracking and tracing information services are the important factors for the intention to use, whereas electronic devices and internet network factors used by the online shops are the main factors for the user behavior. Logistics companies need to provide information services that can help the online shops in controlling their goods in a good way where the ease of access and learning become the main focus that needs attention. Furthermore, online shops need to facilitate their admins with technological devices and a good internet network to make the admins easy to access information services.

Investigations and proposals for data relay satellite systems

<p indent=0mm>After more than ten years of development, China’s data relay satellite (DRS) system has gradually become an efficient space-based information network infrastructure, which provides tracking services and high-bandwidth, near continuous, communications support for users’ many types of spacecraft placed in lower altitude than the geosynchronous orbit. With rapid increase in space activities over the past decades in China, the demand for the DRS system is growing evidently. This paper, mainly from the perspective of application, gives a comprehensive review on the DRS systems worldwide and summarizes the application status of China’s DRS system in these years. Then, we analyze the essence and difficulties of three key bottlenecks in actual DRS system and develop a set of comprehensive and effective solutions for those bottlenecks in the system resource management. Finally, on the basis of refining the application trends of such systems, we give some proposals for future construction and application of China’s DRS system, which includes further completing the system, enhancing the relay satellites’ capabilities, and improving the system operation efficiency. This paper aims to provide global perspectives and technical directions for decision-makers, scholars, and engineers related to the space information network. Moreover, for effectively solving the contradiction between the rapid growth of requirements and limited resources and promoting the capacity of China’s DRS system, we point out the most important development trends, challenges, and work proposals from the perspective of actual applications.

Intelligent System to Find the Health Care Centers for Senior Citizens Based on Disease and Nearest Locations using GPS

It is not convenient nowadays for senior citizens to find an accessible and appropriate health care centre that can meet their needs. Therefore, this initiative helps senior citizens to look for a suitable facility depending on their location and their current illness. The scheme is simple and easily produces results. By using GPS feature or Internet network by using position coordinates and pre-built coordinate databases of nursing care facilities, the details of the nearest facility can be obtained along with the name of the location and buildings with smart phones. The software also provides a tracking service for consumers (senior citizens) so that, by forming a technical relationship with medical centres, it can offer a range of high-quality facilities. The contribution of this system is that through the O2O service, emergency responders can intelligently find a correct hospital that can treat the illness or accident of patients with a smart phone.

Bottom-Up Approach Ship Emission Inventory in Port of Incheon Based on VTS Data

As a result of the rapid growth of international trade, atmospheric pollution from transportation has been more topical than ever, especially in dense hub port-cities. The shipping industry should pay more attention corresponding to its contribution to local atmospheric pollution. This paper supports the application of data collected from the vessel tracking service system with a bottom-up approach to generate a comprehensive 2019 local ship emission inventory at Port of Incheon. The calculated emission inventory presented the dominance of CO2 emission and the considerable contribution of NOx and SOx emissions, the significant contribution of auxiliary engines during the hotelling at berth during the year of 2019. Then, based on calculated emission inventory, this study suggested and simulated applicable green policies in the practice: (1) local emission control area realization, (2) vessel speed reduction program, (3) application of cold ironing, and (4) establishment of a national integrated emission platform. The combination of the three first policies could help reduce the significant volume of emitted CO (29%), NOx (30%), SOx (93%), PM10 and PM2.5 (64%), VOC (28%), NH3 (30%), and CO2 (30%).

A systematic examination of international funding flows for Ebola virus and Zika virus outbreaks 2014–2019: donors, recipients and funding purposes

IntroductionThere has been no systematic comparison of how the policy response to past infectious disease outbreaks and epidemics was funded. This study aims to collate and analyse funding for the...

Identifikasi Elemen Logistik Kota Batam Sebagai Hub Logistik Asean

Kota Batam merupakan salah satu kota yang potensial dikembangkan menjadi Hub Logistik ASEAN. Kondisi geografis yang berupa perbatasan Indonesia dan lokasi yang dekat dengan selat Malaka menjadikan Kota Batam banyak dilalui oleh kapal serta menjadi salah satu jalur logistik yang ramai. Dalam merencanakan pengembangan kualitas logistik maka perlu diketahui elemen prioritas logistik yang menjadi titik tumpu. Penelitian ini menggunakan data primer yang diperoleh dari wawancara serta data sekunder dari jurnal kemudian dianalisa dengan metode deskriptif kualitatif. Data yang diperoleh akan diolah dengan triangulasi, reduksi, penyajian data dan penarikan kesimpulan. Elemen infrastruktur menjadi elemen prioritas yang harus dikembangkan untuk meningkatkan kapasitas dan kapabilititas Kota Batam sebagai Hub Logistik ASEAN. Elemen tersebut dimasukkan pada elemen perencanaan strategic, tactical dan operasional berupa layanan pelanggan, ketersediaan tempat penyimpanan serta kemudahan akses termasuk di dalamnya pengembangan program logistik secara digital. Selain itu elemen tersebut berkaitan erat dengan kemudahan pengiriman, layanan logistik, tracking dan tracing serta mempercepat waktu pengiriman yang dikelola dan dikembangkan oleh BP Batam, Disperindag, PT Pelindo, MRO Hang Nadiem dan PT Citra Shipyard. Elemen kepabean dikelola langsung oleh Bea Cukai sebagai pemegang dan penegakan kebijakan hukum serta identitas lalu lintas barang. Identifikasi elemen logistik dapat menjadi titik ukur perencanaan pengembangan Kota Batam sebagai Hub Logistik ASEAN.

Digitalizing the Closing-of-the-Loop for Supply Chains: A Transportation and Blockchain Perspective

The circular economy is gaining in importance globally and locally. The COVID-19 crisis, as an exceptional event, showed the limits and the fragility of supply chains, with circular economy practices as a potential solution during and post-COVID. Reverse logistics (RL) is an important dimension of the circular economy which allows management of economic, social, and environmental challenges. Transportation is needed for RL to effectively operate, but research study on this topic has been relatively limited. New digitalization opportunities can enhance transportation and RL, and therefore further enhance the circular economy. This paper proposes to review practical research and concerns at the nexus of transportation, RL, and blockchain as a digitalizing technology. The potential benefits of blockchain technology through example use cases on various aspects of RL and transportation activities are presented. This integration and applications are evaluated using various capability facets of blockchain technology, particularly as an immutable and reliable ledger, a tracking service, a smart contract utility, as marketplace support, and as tokenization and incentivization. We also briefly introduce the physical internet concept within this context. The physical internet paradigm proposed last decade, promises to also disrupt the blockchain, transportation, and RL nexus. We include potential research directions and managerial implications across the blockchain, transportation, and RL nexus.

Development of Automated Flight Data Collection System for Air Transportation Statistics

Data and information regarding air transportation is very crucial for all aspects, such as economy, people mobility and tourism. Currently, the Air Transportation Statistics is based on administrative data of different institutions. it is necessary to have a new data source regarding air transportation activities that can be used as an alternative reference for air transportation data which is faster and more granular. This research aims to study a new approach to produce air transportation statistics, especially air transportation statistics in Indonesia from big data that can be used as comparative or as complementary data for official air transportation statistics. This research using a website scraping method from a site that provides monitoring and tracking services for all flights in the world. The flight data was collected daily from the 15 busiest airports in Indonesia for both departure and arrival flights using the API provided by the website. The Scrapy module in the Python programming language is implemented. The data was collected daily from March 15, 2020, to August 31, 2020. The results of the flight data set contain information about the flight code, aircraft code, airline name, departure airport, departure city, arrival airport, arrival city, date/time of departure and arrival, and flight status. The result shows that it is feasible to use big data as a comparative or as a complementary of official statistics, especially in air transportation statistics. By using the web scraping technique, the indicator that usually requires more time and cost can be done in real-time and less cost. This new approach is expected to improve the quality of official air transportation statistics.

The global financial burden of humanitarian disasters: Leveraging GDP variation in the age of climate change

We quantify the global spending burden of humanitarian disaster response. While international response flows are well documented, global domestic spending on disasters is virtually unknown in any comprehensive way. We employ log-log fixed-effects models to estimate international humanitarian disaster response spending as recorded by UNOCHA's Financial Tracking Service (FTS) by recipient country and year, as a function of GDP per capita. Conservatively assuming all humanitarian disaster response spending in the poorest countries originates from without, we calculate a Population Attributable Fraction for the proportion of total spending attributable to GDP per capita, reverse-calculating yearly estimates of total humanitarian disaster response spending. We find global humanitarian expenditures to be roughly 13 times as high as official FTS figures, or around $367 billion annually. Finally, we use Simultaneous Equation Models to examine how total humanitarian disaster response spending is influenced by climate change (proxied by NASA's GISS Surface Temperature data). We find each 1° C rise in 5-year temperature anomalies would require an annual 3.1% (95% CI: 0.18%–6.01%) rise in humanitarian spending. In total, we estimate a further 1° C rise in global temperatures would require total annual humanitarian expenditures of approximately $1 trillion, or about 0.75% of worldwide 2019 GDP, in order to maintain current levels of humanitarian needs coverage. We find climate change to influence humanitarian spending only via GDP per capita and disaster hazard exposure, even though temperature anomalies predict significant increases to disaster vulnerability.