Tag Location Research Articles

Text Coverless Information Hiding Based on the Combination of Chinese Character Components

In recent research works on coverless text information hiding, there are two main problems to be solved: low hiding success rate and small hiding capacity caused by the small amount of redundant information in the cover text. In order to overcome these problems, a method of coverless information hiding based on the combination of Chinese character components is proposed. This method is based on the traditional “location tag [Formula: see text] keywords” mode for coverless information hiding, but with an improved design to extend the scope of available keywords for data hiding beyond the original cover texts. In our proposed method, each Chinese character in the keyword is split into two components: radicals and independent Chinese character, which are collected and will be recombined in pairs to generate the new Chinese characters. This method increases the hiding success rate and hiding capacity by generating Chinese characters that do not exist in the original cover text. The experimental result shows that the proposed method can utilize less size of carrier text database for efficient information hiding. When the size of carrier text database is reduced to 198[Formula: see text]MB, the highest hidden capacity and hidden success that can be achieved are 13.45 and 0.99, respectively.

A potable water location tagging system for victims of natural calamities

In the event of natural calamities and disasters, it is seen that potable water or drinking water becomes an extremely scarce resource. This, in some cases, can lead to very bad situations as seen in the Cholera epidemic in West Bengal (1998), attributed to preceding floods; Hepatitis A and E frequently following heavy rains and floods (Noted in Aceh, Indonesia following December 2004 Tsunami.) But, even in such cases, some uncontaminated local water bodies like cleaner rivers and lakes can be used as a source for drinking water. The project is aimed at designing a system used to identify potable water sources and help the victims of the accident to avail them. This project is designed to get the location of the potable water sources and the victims of the disaster and connect each victim to the nearest potable water source to prevent the scarcity of drinking water. Moreover, it will also prevent the spread of water-borne diseases that are spread when someone consumes water not fit for drinking. This paper is aimed at a project that can target the victims of natural calamities/disasters to their nearest source of safe drinking water to mitigate the risks of post-disaster epidemics and water-borne diseases.

Circular coding: A technique for visual localization in urban areas

The task of visual localization in urban areas is to estimate the location of a camera on a given map by analyzing a street-view image photoed by this camera. Existing methods to accomplish this task perform either a matching between this street-view image and those ones with location tags stored in a database, or a retrieval of structural features of buildings extracted from this street-view image and ‘seen’ from the map. However, the former could fail when there is no database image that has high similarity to the query one, and the latter is generally of high complexity since the retrieval of geometric building information is time-consuming. In this paper, an efficient system for visual localization is developed, which is of the latter category but can achieve real-time performance while delivering high localization accuracy. The core of our developed system is a novel technique termed the circular coding, which is proposed to encode both the street-view image and the map locations with a uniform format, called the coding circle. With this technique, the same location will have the same encoding result in both coding cases, and thus the localization task is simplified to a retrieval process on coding circles that can be efficiently implemented at a low computational expense. Firstly, for each location on the map, the corners of building outlines are projected onto a unit circle to generate a database coding circle. As a result, a coding circle database that consists of all the generated coding circles is constructed. Then, for the camera location, the vertical corner lines (VCLs) of buildings are extracted from the street-view image and also projected onto a unit circle to generate the query coding circle. Finally, owing to a correspondence between the building corners and VCLs, the query location is estimated via a retrieval of its coding circle from the coding circle database. Experimental results show that our localization system is of fast speed and high accuracy, and thus can be used in various applications.

Quantitative Non-Destructive Testing (NDT) of Submerged Civil Concrete Structures Using Remotely Operated Robotic Drones

Periodic inspection is of paramount importance to assess structural integrity and safety. Conventional concrete inspection procedures ranging from rebound hammer, to state-of-the-art ground penetrating radar and ultrasonic tomography focus on superstructures. Often, the part of the structure underwater, is subject to significant levels of corrosion. Today, qualitative visual inspection of the submerged surface can be performed by diving teams, wherein internal defects often go undetected. Furthermore, divers are limited to shallow depths and face several risks, especially when visibility is poor and operating in confined spaces. Presently, there are few commercially available quantitative NDT techniques for submerged structures. This paper presents an alternate solution to inspection of submerged concrete structures — using lightweight remotely operated vehicles (ROV) manufactured by Planys Technologies to perform concrete NDT underwater. Rebound hammer and ultrasonic pulse velocity techniques, although elementary, have been redesigned for use on a submersible drone. Several challenges were addressed including long-range communication and data acquisition, marinizing transducers and pulser-receivers, obtaining measurements in water currents and over deformed surfaces. Planys’ ROVs carry payloads including high-definition cameras, lasers, sonar, and underwater positioning systems to improve data-acquisition quality and location tagging of defects. Key results from experimental studies in a laboratory on canonical specimens are presented. Furthermore, the technology has been successfully tested in a port — details of the structure, operational arrangement and sample results from the field trial are also presented. Following calibration procedures, ROV based underwater concrete NDT was used to acquire data from the structure in grids and subsequently, identify zones of potential non-homogeneity. Numerous challenges, including interpretation of the time traces obtained, and correlation of results to structural integrity and to structures above water, are discussed in the paper. This work will be of interest to asset owners in marine, water management and power generation industries.

PEMANFAATAN FITUR INSTAGRAM SEBAGAI SARANA KOMUNIKASI PEMASARAN KEDAI BABAKKEROYOKAN DI KOTA PALU

This study aims to determine the use of Instagram as a means of marketing communication for Babakkeroyokan in Palu City. This research method is descriptive qualitative by conducting data collection techniques, conducting observations, structured interviews with three informants who have been selected through purposive sampling technique. The number of informants in this study consisted of three informants, namely the owner and holder of the Instagram, the manager of the Instagram, and the Babakkeroyokan sales team. Data analysis techniques used in the form of data collection, data reduction, data presentation, and drawingconclusions. Features Instagram used by Babakkeroyokan have eleven features, namely Profile and Bio Features, Photo and Video Upload Features, Stories Features Caption Features, Comments Features, Hastags Features, Like Features, Activity Features, DirectMessage (DM) Features, Geotagging (Location Tag) Features, and finally the Story Archive Feature. These features are used by Babakkeroyokan as tools to promote their food products to consumers. Features Instagram used by Babakkeroyokan have their respective benefits and uses in helping Babakkeroyokan to promote their food products to consumers, these features are used well by Babakkeroyokan as a means of information to consumers and have benefits for Babakkeroyokan sales in increasing their sales against the same business competition as them. In the use of these features there are interactions with consumers that make communication occur, of the eleven Instagram used by Babakkeroyokan, there are several features that are used every day to promote their food products and interactions with consumers so that communication is established, namely the Story andfeature Direct Message (DM).

Plasticity in the morphometrics and movements of an Antarctic apex predator, the leopard seal

Animals that display plasticity in behavioral, ecological, and morphological traits are better poised to cope with environmental disturbances. Here, we examined individual plasticity and intraspecific variation in the morphometrics, movement patterns, and dive behavior of an enigmatic apex predator, the leopard seal (Hydrurga leptonyx). Satellite/GPS tags and time-depth recorders were deployed on 22 leopard seals off the Western Antarctic Peninsula. Adult female leopard seals were significantly larger (454±59 kg) and longer (302±11 cm) than adult males (302±22 kg, 276±11 cm). As females were 50% larger than their male counterparts, leopard seals are therefore one of the most extreme examples of female-biased sexual size dimorphism in marine mammals. Female leopard seals also spent more time hauled-out on land and ice than males. In the austral spring/summer, three adult female leopard seals hauled-out on ice for 10+ days, which likely represent the first satellite tracks of parturition and lactation for the species. While we found sex-based differences in morphometrics and haul-out durations, other variables, including maximum distance traveled and dive parameters, did not vary by sex. Regardless of sex, some leopard seals remained in near-shore habitats, traveling less than 50 kilometers, while other leopard seals traveled up to 1,700 kilometers away from the tagging location. Overall, leopard seals were short (3.0±0.7 min) and shallow (29±8 m) divers. However, within this general pattern, some individual leopard seals primarily used short, shallow dives, while others switched between short, shallow dives and long, deep dives. We also recorded the single deepest and longest dive made by any leopard seal—1, 256 meters for 25 minutes. Together, our results showcased high plasticity among leopard seals tagged in a single location. These flexible behaviors and traits may offer leopard seals, an ice-associated apex predator, resilience to the rapidly changing Southern Ocean.

Abundance and Migration Success of Overshoot Steelhead in the Upper Columbia River

AbstractSummer steelhead Oncorhynchus mykiss may enter freshwater almost a year before spawning and potentially make long migrations (>1,000 km) to interior headwater habitats. However, in response to suboptimal freshwater habitat conditions (e.g., warmer water temperatures), adult summer steelhead may exhibit complex behaviors during upstream migration in the Columbia River basin. Steelhead may migrate upstream of their natal tributary (hereafter, referred to as “overshoot”) and spend days to several months before subsequently migrating downstream (hereafter, referred to as “fallback”) to their natal tributary to spawn. An expansion of an existing Bayesian patch occupancy model, derived from observations of adult steelhead that were PIT‐tagged to estimate population‐specific abundance upstream of the tagging location, incorporated downstream detection locations to estimate the abundance of overshoot fallbacks. Overshoot steelhead abundance at the tagging location was estimated based on the relationship between the number of known overshoot fallbacks (i.e., the number of steelhead that overshot and successfully migrated downstream to their natal tributary) and their model‐estimated abundance. During the study period (2010–2017), the annual mean proportion of overshoot steelhead that successfully migrated downstream of the tagging location (Priest Rapids Dam) was 0.59 (SD = 0.14). The number of dams encountered by overshoot steelhead during their downstream migration was negatively correlated with their downstream migration success probability. Improved downstream passage survival for adult steelhead will increase the abundance of affected populations while reducing potential genetic introgression of upstream populations (i.e., strays). This is the first study to estimate the abundance of overshoot and fallback steelhead, providing the data necessary for scientists to estimate potential conservation benefits of improved downstream survival. For example, surface flow passage routes (e.g., sluiceways and temporary spillway weirs) are very effective in guiding and passing adult steelhead downstream of Columbia River hydroelectric projects and data from this assessment show that changes in dam operations throughout the downstream migration period may maximize conservation benefits.

First descriptions of the seasonal habitat use and residency of scalloped hammerhead (Sphyrna lewini) and Galapagos sharks (Carcharhinus galapagensis) at a coastal seamount off Japan

BackgroundThe Northwestern Pacific is a data-poor region for studies into the movements and habitat use of open ocean and pelagic sharks. However, this region experiences considerable pressure from commercial fishing. Therefore, shark movement data from this region carry significant implications for conservation and management, particularly for threatened species. Here, we provide the first data on seasonal residency and movements of scalloped hammerhead (Sphyrna lewini) and Galapagos sharks (Carcharhinus galapagensis), using acoustic and satellite telemetry, and dive logbooks, off Japan.ResultsEight female sharks, four of each species, were tagged around a coastal seamount off southeastern Japan (Mikomoto Island) in August 2015, and monitored for a period of up to 363 days using an array of six receivers around the island. Analyses of the more abundant scalloped hammerhead acoustic data suggest high seasonal residency predominantly from August to November associated with lower chlorophyll-a concentrations, before sharks then leave the island and return the following summer. Residency for scalloped hammerhead sharks were highest among those receivers closest to the Kuroshio Current, which produces strong coastal upwelling, however SST was not found to be predictive of occurrence at Mikomoto. Shark presence was corroborated by analysis of dive-log data from a local ecotourism operator. We also produced two unique satellite tracks, whereby a scalloped hammerhead exhibited a 200-km dispersal into a coastal embayment west of the tagging location and a Galapagos shark migrated over 800 km offshore into the high seas.ConclusionThis study provided some of the first behavioral and movement data for scalloped hammerhead and Galapagos sharks in Japan. Our findings suggest varying spatial and temporal visitation of two shark species to a coastal seamount, underscored by some degree of seasonal residency and site fidelity and linked, for scalloped hammerhead sharks at least, to varying productivity. Furthermore, we provided preliminary evidence for long-distance dispersal of these species, and some site fidelity to seamounts in the region. This study highlights the importance of describing shark movements to aid in filling critical data gaps for poorly understood, endemic populations of threatened species.

A Long Story Short: An Analysis of Instagram Stories during the 2020 Campaigns

ABSTRACT Political campaigns are becoming immensely visual, with many platforms, such as YouTube, Instagram, and SnapChat, employed by candidates. We focus on the second most popular platform, Instagram, examining how the 2020 presidential candidates, Donald Trump and Joe Biden, utilize “Stories” in their digital campaigns. Instagram “Stories” allow users to capture and post related images and videos in a slideshow format that disappears after 24-hours. Yet, how did the candidates utilize the Instagram Story technology affordances, such as location tags, stickers, swipe up/websites, and hashtags? What political messages – attack, behind the scenes, or rally - did the candidates use both before and after Election Day? How do the candidates differ in the Story messages? Through the technology affordances lens, we conduct a quantitative content analysis of Instagram Stories posted by Trump and Biden one week before and after Election Day 2020. Our findings reveal how the possible actions or affordances linked to the “Story” feature allow candidates to communicate and engage with users. We conclude by offering a set of industry recommendations when using Instagram Stories in campaigns.

Smart Hospitals and IoT Sensors: Why Is QoS Essential Here?

Background: the increasing adoption of smart and wearable sensors in the healthcare domain empowers the development of cutting-edge medical applications. Smart hospitals can employ sensors and applications for critical decision-making based on real-time monitoring of patients and equipment. In this context, quality of service (QoS) is essential to ensure the reliability of application data. Methods: we developed a QoS-aware sensor middleware for healthcare 4.0 that orchestrates data from several sensors in a hybrid operating room. We deployed depth imaging sensors and real-time location tags to monitor surgeries in real-time, providing data to medical applications. Results: an experimental evaluation in an actual hybrid operating room demonstrates that the solution can reduce the jitter of sensor samples up to 90.3%. Conclusions: the main contribution of this article relies on the QoS Service Elasticity strategy that aims to provide QoS for applications. The development and installation were demonstrated to be complex, but possible to achieve.

Estimating survival in a remote community-based fishery using acoustic telemetry

Small-scale fisheries are often considered data poor due to a myriad of complex factors. Precise estimates of key demographic rates are central to the sustainable management of these fisheries. We used 3 years of acoustic telemetry data to derive survival estimates of Greenland halibut ( Reinhardtius hippoglossoides; n = 255) within a small-scale community fishery in Pangnirtung, Nunavut. Cormack–Jolly–Seber survival estimates were similar for the three top models (quarterly ϕ > 0.80) and detection probability varied with time and as a result of different tag configurations used ( pTag type + t). Survival also differed depending on the location and timing of fish tagging ( ϕCatch; summer vs. winter). A further joint analysis combining detections of live fish and returned tags estimated quarterly survival and site fidelity probability ( s = 0.97, 0.92–1.00 CI (credible interval) and f = 0.96, 0.92–1.00 CI, respectively). Survival estimates were unachievable using traditional tagging methods, highlighting the value of acoustic telemetry mark–recapture as a management tool for estimating demographic parameters for poorly known small-scale fisheries.

Quantifying lung cancer heterogeneity using novel CT features: a cross-institute study

BackgroundRadiomics-based image metrics are not used in the clinic despite the rapidly growing literature. We selected eight promising radiomic features and validated their value in decoding lung cancer heterogeneity.MethodsCT images of 236 lung cancer patients were obtained from three different institutes, whereupon radiomic features were extracted according to a standardized procedure. The predictive value for patient long-term prognosis and association with routinely used semantic, genetic (e.g., epidermal growth factor receptor (EGFR)), and histopathological cancer profiles were validated. Feature measurement reproducibility was assessed.ResultsAll eight selected features were robust across repeat scans (intraclass coefficient range: 0.81–0.99), and were associated with at least one of the cancer profiles: prognostic, semantic, genetic, and histopathological. For instance, “kurtosis” had a high predictive value of early death (AUC at first year: 0.70–0.75 in two independent cohorts), negative association with histopathological grade (Spearman’s r: − 0.30), and altered expression levels regarding EGFR mutation and semantic characteristics (solid intensity, spiculated shape, juxtapleural location, and pleura tag; all p < 0.05). Combined as a radiomic score, the features had a higher area under curve for predicting 5-year survival (train: 0.855, test: 0.780, external validation: 0.760) than routine characteristics (0.733, 0.622, 0.613, respectively), and a better capability in patient death risk stratification (hazard ratio: 5.828, 95% confidence interval: 2.915–11.561) than histopathological staging and grading.ConclusionsWe highlighted the clinical value of radiomic features. Following confirmation, these features may change the way in which we approach CT imaging and improve the individualized care of lung cancer patients.

Machine learning based e-commerce application using progressive web apps for online shopping of seasonal fruits

The key objective of this work is to apply machine learning technique to implement an e-commerce application named eOrchard, a virtual store for online shopping of seasonal fruits. The application is developed using open cart framework, angular and uses the progressive web application development features. Now a days it is very difficult to locate and buy the seasonal fruits around us. The proposed web app will provide information about all kinds of seasonal fruits and facilitates doorstep delivery within a day for locations within the city limits and for location outside the city, delivery can be made within 2 days. Here, the details of all kinds of seasonal fruits are collected along with the geo location tags and stored in the cloud to provide easy access to everyone. Users can order by searching the fruit name or by clicking the city name to know the seasonal fruit that is famous in the selected city. The application provides 24x7 customer support and a step by step tracking system that provide continuous update for the users about the ordered products.

Efficient Wi-Fi Fingerprint Crowdsourcing for Indoor Localization

Wi-Fi Received Signal Strength (RSS, fingerprints) based indoor localization is promising and widely investigated with the pervasive deployment of Wi-Fi Access Points. However, the process to collect RSS, also known as site survey, is labor-intensive. Thus, we propose and demonstrate an efficient fingerprint crowdsourcing method in this paper. Specifically, RSS measurements are obtained and annotated with location tags while a participant is walking along a chosen path with a smartphone at hand. In the localization stage, we adopt the Gaussian Process based solution and propose a novel mean function selection method. Extensive experiments show that the path-based site survey can achieve a comparable localization performance to the point-based site survey, but takes less survey time. We find that fingerprints collected while walking are more suitable for localizing moving pedestrians. In addition, due to the sparsity of fingerprints collected through crowdsourcing, the proposed mean function selection strategy is advantageous and can reduce localization errors significantly compared to a baseline solution.

A Novel Coverless Text Steganographic Algorithm Based on Polynomial Encryption

Aiming at the problems of low text utilization rate and ambiguity of secret information extraction in the “tag + keyword” coverless information hiding methods, we propose a coverless information hiding method of Chinese text based on polynomial encryption in this paper. The secret data communication is realized by the analogously forged URLs transmission, which improves the security of mobile computing to avoid the risk that the carrier texts are attacked maliciously. The text utilization rate and retrieval success rate are improved by using tags to select multiple keywords to expand the number of keywords in the index table. The keyword’s location in secret message is obtained through text vocabulary matching, and the tag index and location information are encrypted by polynomial for secret information transmission. The split keywords of secret message can be transmitted in disorder. The experimental result shows that the secret message can be successfully extracted by sorting the extracted keywords according to the frequency and relevance of their combined tags. In our experiments with different test databases, both the hiding success rate and the average hiding capacity are improved with higher test values than other existing methods.

Research on Architecture of Local Domain Application Based on Radio Frequency Identification

Along with the speedy improvement of sensing systems, wireless transmission technology, and faster and faster chip, the scope of application of the Internet of things (IoT) has substantially and rapidly increased, and research and innovation that integrate artificial intelligence. At same time, campus application construction as the foundation of intelligence education is being on the march, which demands newly emerging computer technologies support, such as IoT, AI, Big data and so on. In this study, we provide an architecture of smart campus based on Radio Frequency Identification (RFID) which can offer new solutions to solve some problems such as position, identification, store information and so on because of its strong anti-interference capability and non-intrusiveness, as core technology of IoT. Then based on this architecture, a kind of intelligent campus application system scheme is proposed, which can realize the function of automatic identity recognition, book reading, internal consumption, student positions. Moreover, for some special exact location demands, this paper proposes a method to precisely measure RFID tag location based on triangulation principle, which is embedded in the architecture. The application of Internet of things technology can better promote some origination or company efficiency, such as more efficient service for teachers’ and students’ work, study and life.

Coherent Multiantenna Receiver for BPSK-Modulated Ambient Backscatter Tags

Ambient backscatter communication (AmBC) is an emerging communication technology enabling green Internet of Things deployments. The widespread acceptance of this paradigm is limited by the low signal-to-interference-plus-noise ratio (SINR) of the signal impinging on the receiver antenna due to the strong direct path interference and unknown ambient signal. The adverse impact of these two factors can be mitigated by using noncoherent multiantenna receivers, which are known to require a higher SINR to reach the bit-error-rate (BER) performance of coherent receivers. However, considering the unknown ambient signal, unknown location of AmBC tags, and varying channel conditions, coherent receivers for AmBC systems are rarely studied in the literature. In this article, a coherent multiantenna receiver, which requires no prior information of the ambient signal for decoding the binary-phase-shift-keying (BPSK) modulated signal, is presented. The performance of the proposed receiver is compared with an ideal coherent receiver that has perfect phase information, and also with the performance of a noncoherent receiver, which assumes distributions for ambient signal and phase offset caused by the excess length of the backscatter path. Comparative simulation results show the designed receiver can achieve the same BER performance of the ideal coherent receiver with 1-dB more SINR, which corresponds to 5-dB or more gain with respect to noncoherent reception of on-off-keying modulated signals. Variation in the detection performance with the tag location shows that the coverage area is in the close vicinity of the transmitter and a larger region around the receiver, which is consistent with the theoretical results.

Tag-based visual-inertial localization of unmanned aerial vehicles in indoor construction environments using an on-manifold extended Kalman filter

Automated visual data collection using autonomous unmanned aerial vehicles (UAVs) can improve the accessibility and accuracy of the frequent data required for indoor construction inspections and tracking. However, robust localization, as a critical enabler for autonomy, is challenging in ever-changing, cluttered, GPS-denied indoor construction environments. Rapid alterations and repetitive low-texture areas on indoor construction sites jeopardize the reliability of typical vision-based solutions. This research proposes a tag-based visual-inertial localization method for off-the-shelf UAVs with only a camera and an inertial measurement unit (IMU). Given that tag locations are known in the BIM, the proposed method estimates the UAV's global pose by fusing inertial data and tag measurements using an on-manifold extended Kalman filter (EKF). The root-mean-square error (RMSE) achieved in our experiments in laboratory and simulation, being as low as 2 − 5 cm, indicates the potential of deploying the proposed method for autonomous navigation of low-cost UAVs in indoor construction environments.

Invisible Geolocation Signature Extraction From a Single Image

Geotagging images of interest are increasingly important to law enforcement, national security, and journalism. Today, many images do not carry location tags that are trustworthy and resilient to tampering; and landmark-based visual clues may not be readily present in every image, especially in those taken indoors. In this paper, we exploit an environmental signature from the power grid, the electric network frequency (ENF) signal, which can be inherently captured in a sensing stream at the time of recording and carries useful time&#x2013;location information. Compared to the recent art of extracting ENF traces from audio and video recordings, it is very challenging to extract an ENF trace from a single image. We address this challenge by first mathematically examining the impact of the ENF embedding steps such as electricity to light conversion, scene geometry dilution of radiation, and image sensing. We then incorporate the verified parametric models of the physical embedding process into our proposed entropy minimization method. The optimized results of the entropy minimization are used for creating a two-level ENF presence&#x2013;classification test for region-of-capturing localization. It identifies whether a single image has an ENF trace; if yes, whether it is at 50 or 60 Hz. We quantitatively study the relationship between the ENF strength and its detectability from a single image. This paper is the first comprehensive work to bring out a unique forensic capability of environmental traces that shed light on an image&#x2019;s capturing location.

The Local Service Solution: A Business Transformation of Traditional Media Companies

In this paper, by analyzing the fierce competition challenges faced by traditional media companies in the era of integrated media, combined with the transformation and development direction of traditional media companies, the Local Service Solution based on geographic information coordinate system is designed creatively, which provides a feasible path for traditional media companies to effectively deal with the challenges of fierce competition and explore the benefits of diversification. The innovation of the Local Service Solution is that it is divided into two sub-parts: e-commerce and community service, while e-commerce is the core economic unit of the solution. In e-commerce applications, the existing media assets and new programs, short videos, live broadcasts and other forms will be combined to effectively realize the accurate development and commercial realization of digital assets. The community service section is the social value unit of the solution. Through geographical location tags and specific applications, it provides grid-based media news for the community, politics, consultation and other services for citizens, and becomes an important communication channel for citizens to exercise upward supervision power.