Missing People Research Articles

Design & Development of An Web Application for Tracking and Deducting Missing Person

The Missing Persons Comprehensive Tracking System is a robust solution designed to improve the efficiency of tracking missing persons. Its secure login-based interface allows authorized users to manage missing people data effectively. By integrating multiple CCTV feeds and a database of found person details, the system enhances real-time surveillance and enables quick identification. The proximity-based police station mapping feature further facilitates prompt response and coordination, making it a valuable tool for law enforcement agencies and other stakeholders involved in locating missing individuals.

'Here we Punish, Here we Discipline': Forced Displacement, Silencing and the Multiple Faces of Violence in Cabo Delgado, Mozambique

Forced displacement and silencing are inextricably bound for communities who have experienced different forms of violence in different contexts. This article explores the narratives about the war that began on 5 October 2017 in the district of Mocímboa da Praia, on the coast of the province of Cabo Delgado, northern Mozambique, by a group of radical guerrillas locally known as mashababe. Since then, from isolated attacks on remote villages, violence has spread to more districts in the region, with kidnappings of civilians, looting of barns and houses, thus imposing the forced displacement of hundreds of thousands of people in addition to an inestimable number of dead and missing people. This article combines the history and ethnographic work carried out between 2018 and 2021 with the homeless populations from conflict regions and hosted in the 'Nacaca Displaced Persons Camp' (Campo de Deslocados de Nacaca), built in the district of Montepuez, south of Cabo Delgado, a region previously considered safe. The aim of this paper is to analyse how the multiple faces of traumatic violence (physical, psychological and symbolic) are processed in which war victims are continually exposed through silencing imposed by different actors who frequent their new places of refuge.

Finding Missing Person Using Face Recognition

Abstract: This project presents a novel approach to enhance the efficiency and effectiveness of locating missing persons through the utilization of face recognition technology The main objective is to develop a robust system that can extract facial features, match them with a database, and notify the missing person's location. The system uses a special type of artificial intelligence called CNN to compare faces with the database and find the best matches. The face recognition system uses the CNN (Convolutional Neural Network) algorithm to compare the extracted faces with the database and find the best matches. The alert module sends notifications to the family members of the missing person with the location information if a match is found. The system also updates the database with the latest information about the missing person. The project leverages state-of-the-art machine learning algorithms to extract and compare facial features, it reduces the effort and time required for manual process. This project aims to find missing people faster and better by using facial recognition technology. The main goal is to build a strong system that can study facial details, match them with a database of known people, and help to find missing people quickly and correctly. By harnessing the power of artificial intelligence, this system offers a promising solution to the pressing issue of finding missing individuals, potentially helping to reunite families and improve public safety.

Biogeographical Ancestry Analyses Using the ForenSeqTM DNA Signature Prep Kit and Multiple Prediction Tools.

The inference of biogeographical ancestry (BGA) can assist in police investigations of serious crime cases and help to identify missing people and victims of mass disasters. In this study, we evaluated the typing performance of 56 ancestry-informative SNPs in 177 samples using the ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system. Furthermore, we compared the prediction accuracy of the tools Universal Analysis Software v1.2 (UAS), the FROG-kb, and GenoGeographer when inferring the ancestry of 503 Europeans, 22 non-Europeans, and 5 individuals with co-ancestry. The kit was highly sensitive with complete aiSNP profiles in samples with as low as 250pg input DNA. However, in line with others, we observed low read depth and occasional drop-out in some SNPs. Therefore, we suggest not using less than the recommended 1ng of input DNA. FROG-kb and GenoGeographer accurately predicted both Europeans (99.6% and 91.8% correct, respectively) and non-Europeans (95.4% and 90.9% correct, respectively). The UAS was highly accurate when predicting Europeans (96.0% correct) but performed poorer when predicting non-Europeans (40.9% correct). None of the tools were able to correctly predict individuals with co-ancestry. Our study demonstrates that the use of multiple prediction tools will increase the prediction accuracy of BGA inference in forensic casework.

Missing Person and Criminal Identification using Image Processing

In the world, a countless number of people are missing every day which includes kids, teens, mentally challenged, old-aged people with Alzheimer's, etc. Most of them remain untraced. To this missing case entry is updated in police station. By using web camera technology compare each person with the available database and find these people. This system designed to find the missing people.[11] If the missing person found in the Web Video streaming then send the location of missing person to police station. After missing person found in the Web Video streaming, send location Email to Police station. So our system can perform the very important role in security and authentication issues. Here the admin perform the all administrative role in this system. Admin can add the user police, remove the user police and view the user police. The system detects the results and generates output accordingly. This will make the work of police to find a particular person easier.[12].

Visualizing a ‘missing people’ in Sousa Dias’ Still Life: The filmmaker as metallurgist

Drawing from Deleuze and Guattari’s geophilosophy, Patricia Pisters adopts the term ‘metallurgical’ to describe the filmmaking of contemporary directors of political cinema who exploit the unprecedented opportunities afforded by digital technology to recycle and remediate transnational visual archives. Similarly, in the light of Deleuze’s meditations on modern film in Cinema 2: The Time-Image (1989), Pisters identifies metallurgical filmmaking with the ‘forging’ of a supra-national ‘world memory’ and a liberated ‘people to come’. My interest in this article is to ponder the extent to which these concepts might be useful for analysing the intermedial documentaries of Portuguese filmmaker, Susana de Sousa Dias (1962–present). More specifically, I am interested in exploring how Sousa Dias’ work with archival photographs of political prisoners in her early film Still Life (2005) might suggest both an ‘interruption’ of a chronological national history and, at the same time, an appeal to the suppressed social memory of a ‘missing people’ from Portugal’s dictatorial past. To elucidate this premise, I propose that the mugshots function as symbolic counterpoints to the transcontinental ‘patriotic masses’ of regime propaganda with which they are intercut in the film. By extension, I also propose that they evoke the de-individuated memorial consciousness associated with a ‘world memory’.

The forensic imaging technique of age progression used within missing people cases: The Italian Missing Children association realizing age progression for Missing Child Kenya

The age progression technique allows to update identification photos of individuals who have been missing for years. This method is based on the study of the facial variation and on the dynamics of facial growth. Knowledge about changes in the distribution of facial fat and the tone of the cartilage allows realistic predictions of the facial appearance after many years. Beside these elements, age progression is also supported by similar characters between family members. This is why photos of the missing and family members are used to create an age progression, making the new identikit accurate.Non-profit associations are crucial for the dissemination of information on the problem of missing persons. In Italy, the Italian Missing Children association provides for free an age progression service with the support of forensic anthropology. With the activation of a protocol, consisting of guidelines, and a form for the request for age progression by family members, the Italian Missing Children has started a collaboration with Missing Child Kenya. It allowed to disseminate up-to-date photos of the presumed current appearance of the missing children in Kenya. Thus, in the present study some cases are reported, in which age progression technique was applied.The photos provided by Italian Missing Children were shown in video documentaries made by Missing Child Kenya, allowing to continue the dissemination of age progression photo during the Covid quarantines and to keep the population active in the search for the missing.

An Integrated YOLOv5 and Hierarchical Human-Weight-First Path Planning Approach for Efficient UAV Searching Systems

Because the average number of missing people in our country is more than 20,000 per year, determining how to efficiently locate missing people is important. The traditional method of finding missing people involves deploying fixed cameras in some hotspots to capture images and using humans to identify targets from these images. However, in this approach, high costs are incurred in deploying sufficient cameras in order to avoid blind spots, and a great deal of time and human effort is wasted in identifying possible targets. Further, most AI-based search systems focus on how to improve the human body recognition model, without considering how to speed up the search in order to shorten the search time and improve search efficiency, which is the aim of this study. Hence, by exploiting the high-mobility characteristics of unmanned aerial vehicles (UAVs), this study proposes an integrated YOLOv5 and hierarchical human-weight-first (HWF) path planning framework to serve as an efficient UAV searching system, which works by dividing the whole searching process into two levels. At level one, a searching UAV is dispatched to a higher altitude to capture images, covering the whole search area. Then, the well-known artificial intelligence model YOLOv5 is used to identify all persons in the captured images and compute corresponding weighted scores for each block in the search area, according to the values of the identified human bodies, clothing types, and clothing colors. At level two, the UAV lowers its altitude to sequentially capture images for each block, in descending order according to its weighted score at level one, and it uses the YOLOv5 recognition model repeatedly until the search target is found. Two improved search algorithms, HWFR-S and HWFR-D, which incorporate the concept of the convenient visit threshold and weight difference, respectively, are further proposed to resolve the issue of the lengthy and redundant flight paths of HWF. The simulation results suggest that the HWF, HWFR-S, and HWFR-D search algorithms proposed in this study not only effectively reduce the length of a UAV’s search path and the number of search blocks but also decrease the search time required for a UAV to locate the search target, with a much higher search accuracy than the two traditional search algorithms. Moreover, this integrated YOLOv5 and HWF framework is implemented and tested in a real scenario to demonstrate its capability in enhancing the efficiency of a search and rescue operation.

The Missing Person in a Story about Kashmir: A Reading of Madhuri Vijay’s <i>The Far Field </i>

This article examines the trope of the ‘missing person’ in the literature about Kashmir and argues, by taking Madhuri Vijay’s The Far Field (2019) as an example, how the trope allows the examination of a multilayered history of violence. The article problematises the idea of visibility and invisibility of the missing/abducted/hidden/underground people during conflict and suggests that these figures can be read as metaphors for personal and collective trauma and loss. By triangulating three coordinates in Kashmiri context – violence, trauma, and invisibility – the essay argues that a missing person can be emblematic of memories of trauma, negation of humanity, violation of body, and public complicity in institutional violence. By foregrounding Shalini’s journey to recover the missing people, the novel underpins the “rot remains” of a society afflicted with violence and state apathy. Within the framework of trauma theory in the postcolonial context, the essay shows how the focus of Vijay’s narrative of Kashmiri people’s trauma is shifted from speech to body. The emphasis on the body contributes to a compelling narration of trauma by conflating land and people.

Housing Pathways of the “Missing People” of Public Housing and Resettlement Programs: Methodological Reflections

This article deals with methodological challenges and presents solutions for the study of people who depart from state-subsidized housing in Ethiopia, Morocco, and South Africa. Having sold or rented out their units, these people have left and now live at dispersed locations. Assuming that many “missing people” leave state housing because of project-related shortcomings, studying the reasons for their departure is crucial to understanding standardized housing programs. “Missing people” urge scholars to emphasize the afterlives of housing policy interventions as a necessary analytical dimension. However, such research is confronted with three major methodological challenges: How is it possible to approach and study people who have disappeared from the area of a housing intervention? How can one link exploratory, in-depth qualitative accounts, rooted in subjective perceptions of the everyday, to potential structural deficiencies of standardized housing interventions? What kind of methodologies may help take into account the temporalities of displacement and resettlement? In order to overcome these challenges, the article presents innovative forms of purposive sampling and discusses analytical strategies, which—based on Clapham’s framework of “housing pathways”—bridge relational and structural perspectives to housing programs.

Prevalence and incidence of symptomatic pulmonary tuberculosis based on repeated population screening in a district in Ethiopia: a prospective cohort study

ObjectiveIn Ethiopia, one-third of the estimated tuberculosis cases are not detected or reported. Incidence estimates are inaccurate and rarely measured directly. Assessing the ‘real’ incidence under programme conditions is useful...

All that glitters is not gold: X-ray fluorescence analysis of a fixed dental prosthesis from Colecção de Esqueletos Identificados Século XXI, Portugal (CEI/XXI)

Access to better health care anticipates that more medical devices can be found alongside skeletal remains. Those employed in oral rehabilitation, with available brands or batch/series, can prove useful in the identification process. A previous study in the Colecção de Esqueletos Identificados Século XXI described macroscopically the dental prostheses. An unusual case of a dental device with chromatic alterations demonstrated to require a more detailed analysis. The individual, a 53-year-old male, exhibited, at both arches, a fixed tooth-supported rehabilitation, with gold colouring classified initially as a gold-palladium alloy. Simultaneously, a green pigmentation deposit was observable in bone and prosthesis. This investigation aimed to verify the elemental composition of the dental prosthesis alloy. Elemental analysis was performed by X-ray fluorescence in two regions (labial surface of the prosthetic crown and the root surface of the lower right lateral incisor). Both the spectra and the qualitative results found higher levels of copper and aluminium, followed by nickel, iron, zinc, and manganese. No gold or palladium was detected. The most probable assumption is that a copper-aluminium alloy was used, as its elemental concentration corresponds to those measured in similar devices. Dental prostheses of copper-aluminium alloys have been made popular since the 1980s, particularly in the USA, Japan, and Eastern Europe. Apart from the biographical information, it was also known that the individual’s place of birth was an Eastern European country, which highlighted the usefulness of this type of information when dealing with missing people cases.

Population analysis of complete mitogenomes for 334 samples from El Salvador

The use of mitochondrial DNA (mtDNA) in the field of forensic genetics is widely spread mainly due to its advantages when identifying highly degraded samples. In this sense, massive parallel sequencing has made the analysis of the whole mitogenome more accessible, noticeably increasing the informativeness of mtDNA haplotypes. The civil war (1980–1992) in El Salvador caused many deaths and disappearances (including children) all across the country and the economic and social instability after the war forced many people to emigration. For this reason, different organizations have collected DNA samples from relatives with the aim of identifying missing people. Thus, we present a dataset containing 334 complete mitogenomes from the Salvadoran general population. To the best of our knowledge, this is the first publication of a nationwide forensic-quality complete mitogenome database of any Latin American country. We found 293 different haplotypes, with a random match probability of 0.0041 and 26.6 mean pairwise differences, which is similar to other Latin American populations, and which represent a marked improvement from the values obtained with just control region sequences. These haplotypes belong to 54 different haplogroups, being 91% of them of Native American origin. Over a third (35.9%) of the individuals carried at least a heteroplasmic site (excluding length heteroplasmies). Ultimately, the present database aims to represent mtDNA haplotype diversity in the general Salvadoran populations as a basis for the identification of people that disappeared during or after the civil war.

Finding Missing Person Based on Face Recognition Using AI in Video Surveillance System

Abstract: AI-based face recognition for missing person searches is a promising strategy that has the potential to significantly speed up and improve accuracy. The system makes use of artificial intelligence algorithms to match surveillance camera realtime video footage with facial images of people who have gone missing. Face recognition technology in video surveillance systems is used in this project to come up with a strategy for locating people who have gone missing. The system involves gathering information about the missing person, creating a database of facial images, and matching those images to real-time video footage with the help of artificial intelligence algorithms. The goal of the field of computer science known as artificial intelligence (AI) is to create intelligent machines that can carry out tasks that typically call for human intelligence. This includes tasks like translating languages, visual perception, speech recognition, and decision-making. Machine learning algorithms are used by AI systems to learn from data and allow them to improve their performance over time. A powerful method for training artificial neural networks with many layers, deep learning, a subset of machine learning, has emerged, allowing. The system can be used to quickly identify and locate missing people in public places like airports and train stations. The speed and accuracy of missing person searches could be significantly enhanced by the proposed system, increasing the likelihood of successful reunions. Finding missing people in view of face acknowledgment utilizing Convolutional Brain Organization (CNN) calculation is a well-known approach that has shown promising outcomes. CNN is a deep learning algorithm that works well for face recognition because it is widely used for image recognition and classification.

A search and rescue robot device realization based on ROS operating system combined with visual algorithm

Aiming at the problem of low accuracy of intelligent devices to find missing people, a search and rescue robot device based on ROS intelligent navigation system was proposed. SolidWorks was used to improve the new mechanical structure that can switch autonomously to different terrain and combined with Yolov5 deep learning algorithm to complete face recognition. Using the stm32 single-chip microcomputer, we adjusted the cascade PID parameters of the motor and simulation to realize the omnidirectional movement control of the robot. Through the analysis and verification of the experimental data, the adaptive ability of the improved robot platform to the terrain was significantly improved. The method can accurately complete the task of face recognition and autonomous navigation, which is practical and improves the accuracy of finding the missing people.

Suhail: A Deep Learning-Based System for Identifying Missing People

Many people become missing in Saudi Arabia every day, including children, young people, and the mentally ill as well as the elderly with Alzheimer’s. There are many missing people cases that are still unsolved. In Saudi Arabia, people use social media platforms such as Twitter to report missing people cases. The application of deep learning has been successful in a wide range of fields including computer vision and machine vision. In particular, face recognition techniques are effective in saving time and effort, especially when searching for missing individuals. Hence, the goal of this research is to solve this issue by developing a deep learning-based system for identifying missing individuals. This paper introduces a new system called Suhail. The system has been implemented and developed using Android Studio and open-source libraries such as TensorFlow. First, users or governments can report missing persons by uploading photos. Updates and information will then be shared with the rest of the system’s users (volunteers). Once a volunteer discovers a suspect, they scan their face using camera. Then, our application uses face recognition techniques to compare the suspect's photo with photos from the repository. Finally, once a comparison is found, our application contacts the suspect’s family, informs them of his location and then notifies the police that a missing person has been located. By using our application and face recognition systems, we help families and police locate and reach a missing person which saves time and effort. In this study, 759 participants were enrolled to evaluate the performance of the Suhail system. Engagement, aesthetics, and functionality are used to evaluate the user experience. The results of the experiment show that users enjoy the new features of the application and that the system is simple to use. Moreover, the system would help governments and individuals identify missing people faster.

Where are the missing people affected by tuberculosis? A programme review of patient-pathway and cascade of care to optimise tuberculosis case-finding, treatment and prevention in Cambodia

BackgroundCambodia has achieved great success in tuberculosis (TB) control in the past decade. Nevertheless, people with TB are missed by the health systems at different stages of the care pathway....

Ethical Hacking for a Good Cause: Finding Missing People using Crowdsourcing and Open-Source Intelligence (OSINT) Tools

Over 600,000 people go missing every year in the US alone. Despite the extensive resources allocated to investigating these cases, the high volume of missing person cases constitutes one of the biggest challenges for law enforcement agencies. One approach to tackle this challenge is using crowdsourcing. That is, volunteers use freely available tools and techniques to aid the existing efforts to investigate missing person cases. Open-Source Intelligence (OSINT) refers to gathering information from publicly available sources and analyzing it through a comprehensive set of open-source tools to produce meaningful and actionable intelligence. OSINT has been applied to address various societal challenges and crimes, including environmental abuse, human rights violations, child exploitation, domestic violence, disasters, and locating missing people. Building on this premise, this case examines a crowdsourced initiative called Trace Labs that aims to assist law enforcement agencies in solving missing person cases using OSINT tools. The case emphasizes socio-technical aspects of cybersecurity, highlighting both the bright and dark sides of technology. It demonstrates the potential of information systems to serve the public good by examining topics such as open-source software, crowdsourcing, and intelligence gathering, while acknowledging that the very same underlying technology can be used for malicious purposes.

Tracking missing persons using facial recognition

Finding missing people is a time-critical and labor-intensive task and the longer it takes to locate the person, the lower the likelihood of a successful outcome. To address this challenge, an integrated and centralized database of missing persons using Aadhar card details was developed. The approach incorporates facial recognition technology, specifically the deep face algorithm, which has shown high accuracy in identifying individuals. While facial recognition has been in use for several years, recent advancements have made it easier to identify individuals accurately. By leveraging Artificial Intelligence (AI) powered facial recognition technology, officials can enhance and streamline the process of finding, tracking, and retrieving missing persons. The system matches facial features with the data stored in Aadhar cards, providing a reliable means of identification. This research presents a system that centralizes data, improving the efficiency of locating missing individuals. By utilizing facial recognition and centralizing data, the system offers an efficient approach to find missing people. The integration of technology and data allows quick and more accurate identification, increasing the chances of locating missing persons promptly.

The role of postmortem bone analysis in identifying missing people: a case report

The role of postmortem bone analysis in identifying missing people: a case report