Search results for: human detection and identification

Authors: Aika Umemuro, Mitsuru Sato, Mizuki Narita, Saya Hori, Saya Sakurai, Tomomi Nakayama, Ayano Nakazawa, Toshihiro Ogura

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Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.

Keywords: EEG scanner, eye-detector, mammography, observers

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Authors: Hao Mi, Ming Yang, Tian-yue Yang

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Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

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Authors: Alena Skalon, Jennifer L. Beaudry

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Eyewitness misidentifications can sometimes lead to wrongful convictions of innocent people. This occurs in part because jurors tend to believe confident eyewitnesses even when the identification took place under suggestive conditions. Empirical research demonstrated that jurors are often unaware of the factors that can influence the reliability of eyewitness identification. Most common legal safeguards that are designed to educate jurors about eyewitness evidence are judicial instructions and expert testimony. To date, very few studies assessed the effectiveness of judicial instructions and most of them found that judicial instructions make jurors more skeptical of eyewitness evidence or do not have any effect on jurors’ judgments. Similar results were obtained for expert testimony. However, none of the previous studies focused on the ability of legal safeguards to improve jurors’ assessment of evidence obtained from suggestive identification procedures—this is one of the gaps addressed by this paper. Furthermore, only three studies investigated whether legal safeguards improve the ultimate accuracy of jurors’ judgments—that is, whether after listening to judicial instructions or expert testimony jurors can differentiate between accurate and inaccurate eyewitnesses. This presentation includes two studies. Both studies used genuine eyewitnesses (i.e., eyewitnesses who watched the crime) and manipulated the suggestiveness of identification procedures. The first study manipulated the presence of judicial instructions; the second study manipulated the presence of one of two types of expert testimony: a traditional, verbal expert testimony or expert testimony accompanied by visual aids. All participant watched a video-recording of an identification procedure and of an eyewitness testimony. The results indicated that neither judicial instructions nor expert testimony affected jurors’ judgments. However, consistent with the previous findings, when the identification procedure was non-suggestive, jurors believed accurate eyewitnesses more often than inaccurate eyewitnesses. When the procedure was suggestive, jurors believed accurate and inaccurate eyewitnesses at the same rate. The paper will discuss the implications of these studies and directions for future research.

Keywords: expert testimony, eyewitness evidence, judicial instructions, jurors’ decision making, legal safeguards

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Authors: Faith G. Ehiemua, Chandra E. Ulinfun

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This work presents two approaches that use competing models to combat criminality in human trafficking. It argues that oath-taking is an approach used to combat and repress crime by natives of African descent. Therefore, certain value choices reflected explicitly or implicitly in its habitual functioning are features of crime control, a model of the criminal process used to repress and prevent crime. By pitting the approaches against each other, the work examines the utility of the purpose of each approach with the aim of assessing moral worthiness. The approaches adopted are descriptive, normative, and theoretical. The findings reveal that oath-taking is effective in human trafficking mainly because Africans believe that the African traditional system is efficient. However, the utilitarian ethical theory applied to the use of oath-taking in human trafficking shows oath-taking as protecting the interest of human traffickers against the general good of society.

Keywords: human rights, human trafficking, oath taking, utilitarianism, victim-centered approach

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: Mohamed A. Alhammad, Hadia A. Abou-Donia, Mona H. Hashish, Mohamed N. Massoud

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Background: Rotavirus is the leading etiologic agent of severe diarrheal disease in infants and young children worldwide. The present study was aimed 1) to detect rotavirus infection as a cause of diarrhoea among children under 5 years of age using the two serological methods (ELISA and LA) and the PCR technique (2) to evaluate the three methodologies used for human RV detection in stool samples. Materials and Methods: This study was carried out on 247 children less than 5 years old, diagnosed clinically as acute gastroenteritis and attending Alexandria University Children Hospital at EL-Shatby. Rotavirus antigen was screened by ELISA and LA tests in all stool samples, whereas only 100 samples were subjected to RT-PCR method for detection of rotavirus RNA. Results: Out of the 247 studied cases with diarrhoea, rotavirus antigen was detected in 83 (33.6%) by ELISA and 73 (29.6%) by LA, while the 100 cases tested by RT-PCR showed that 44% of them had rotavirus RNA. Rotavirus diarrhoea was significantly presented with a marked seasonal peak during autumn and winter (61.4%). Conclusion: The present study confirms the huge burden of rotavirus as a major cause of acute diarrhoea in Egyptian infants and young children. It was concluded that; LA is equal in sensitivity to ELISA, ELISA is more specific than LA, and RT-PCR is more specific than ELISA and LA in diagnosis of rotavirus infection.

Keywords: rotavirus, diarrhea, immunoenzyme techniques, latex fixation tests, RT-PCR

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Authors: Jorge R. Santos, Pedro Sebastiao

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In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

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Authors: Usama Shahid

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Be it written documents, news columns, or students' essays, verifying the content can be a time-consuming task. Apart from the spelling and grammar mistakes, the proofreader is also supposed to verify whether the content included in the essay or document is relevant or not. The irrelevant content in any document or essay is referred to as off-topic text and in this paper, we will address the problem of off-topic text detection from a document using machine learning techniques. Our study aims to identify the off-topic content from a document using Echo state network model and we will also compare data with other models. The previous study uses Convolutional Neural Networks and TFIDF to detect off-topic text. We will rearrange the existing datasets and take new classifiers along with new word embeddings and implement them on existing and new datasets in order to compare the results with the previously existing CNN model.

Keywords: off topic, text detection, eco state network, machine learning

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Authors: M.Younus, M. Athar Khan, Asif Adrees

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The present research endeavour was made to investigate the Public Health impact of Salmonellosis through consuming the meat and eggs of the carrier’s birds and to see the prevalence of Salmonella enteritidis and Salmonella typhimurium from poultry feed, poultry meat, and poultry eggs and their role in the chain of transmission of salmonellae to human beings and causing food poisoning. The ultimate objective was to generate data to improve the quality of poultry products and human health awareness. Salmonellosis is one of the most wide spread food borne zoonoses in all the continents of the world. The etiological agents Salmonella enteritidis and Salmonella typhimurium not only produce the disease but during the convalescent phase (after the recovery of disease) remain carriers for indefinite period of time. The carrier state was not only the source of spread of disease with in the poultry but also caused typhoid fever in humans. The chain of transmission started from poultry feed to poultry meat and ultimately to humans as dead end hosts. In this experiment a total number of 200 samples of human stool and blood were collected randomly (100 samples of human stool and 100 samples of human blood) of 100 patients suspected from food poisoning patients from different hospitals of Lahore area for the identification of Salmonella enteritidis and Salmonella typhimurium through PCR method in order to see the public health impact of Salmonellosis through consuming the meat and eggs of the carrier birds. On the average 14 and 10 stool samples were found positive against Salmonella enteritidis and Salmonella typhimurium from each of the 25 patients from each hospital respectively in case of suspected food poisoning patients. Similarly on an average 5% and 6% blood samples were found positive from 25 patients of each hospital respectively. There was a significant difference (P< 0.05) in the sero positivity of stool and blood samples of suspected food poisoning patients as far as Salmonella enteritidis and Salmonella typhimurium was concerned. However there was no significant difference (P<0.05) between the hospitals.

Keywords: salmonella, zoonosis, food, transmission, eggs

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Authors: O. O. Fola-Matthews, O. O. Soyinka, D. N. Bitalo

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Nigeria is one of the major shark fishing nations in Africa, but its fisheries managers still record catch data in aggregates ‘sharks’ with no species-specific details. This is because most of the shark specimens look identical in morphology, and field identification of some closely related species is tricky. This study uses DNA barcoding as a method to identify shark species from five different landing areas off the Nigerian Coast. 100 dorsal fins were sampled in order to provide a Chondrichthyan sequence that would be matched to reference specimens in a DNA barcode database

Keywords: BOLD, DNA barcoding, nigeria, sharks

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Authors: Miftahuddin Khilji

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The concept of human right is not alien to Islam. The Shari‘ah requires all its followers the sense of responsibility to perform their duties first and then claim their rights. This eventually guarantees the protection of human rights and ensures a peaceful society. The ultimate goal of Shari‘ah is to preserve five basic necessities which are also known as Maqasid ul Shari‘ah or Objectives of Islamic Law. This goal ensures for the members of society their rights without harming public welfare. Despite of the fact that human rights have been fully guaranteed by Islam and their compliance is required by Allah Almighty; not by any legislative body or other sovereign such as kings etc. However, many western writers, organizations and so called liberal thinkers try to create concerns, doubts and misconceptions in minds of the society members. A number of issues are pointed out and people are misguided about the concept of human rights in Islam. This paper aims to discuss main the concept of human rights in the light of perfect and balanced system of laws and principles of Shari‘ah and address those misconceptions and doubts by analyzing them and answering to questions raised about the subject. It would be an effort to prove that human rights are much more significant to Shari‘ah more than any other national or international legislative body.

Keywords: human rights, Islamic law, law, Shariah

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Authors: Zhang Xingnan, Huang Jingjia, Feng Yue, Burra Venkata Durga Kumar

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This paper proposes a comprehensive approach to mitigate ROP (Return-Oriented Programming) attacks by combining internal operating system protection mechanisms and hardware-assisted techniques. Through extensive literature review, we identify the effectiveness of ASLR (Address Space Layout Randomization) and LBR (Last Branch Record) in preventing ROP attacks. We present a process involving buffer overflow detection, hardware-assisted ROP attack detection, and the use of Turing detection technology to monitor control flow behavior. We envision a specialized tool that views and analyzes the last branch record, compares control flow with a baseline, and outputs differences in natural language. This tool offers a graphical interface, facilitating the prevention and detection of ROP attacks. The proposed approach and tool provide practical solutions for enhancing software security.

Keywords: operating system, ROP attacks, returning-oriented programming attacks, ASLR, LBR, CFI, DEP, code randomization, hardware-assisted CFI

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

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Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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Authors: Mallikarjun Warad, C. M. Kalleshwaraswamy, P. R. Shashank

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Studies were conducted to record the occurrence of different species of hairy caterpillar on different host plants in and around Shivamogga, Karnataka, India. Twelve genera of hairy caterpillars belonging to Arctiinae and Lymantriinae were recorded on different host plants and reared to adults in laboratory on their respective hosts. The Porthesia sp. feed on castor, Creatonotus gangis on cocoa, Perina nuda on fig, Pericalia ricini on pigeon pea, Utetheisa pulchella on sunhemp and Euproctis sp. on paddy and banana. Illustrations of immature and adults were made to associate them. Along with this, light traps were also set during the rainy season, to capture adults of hairy caterpillars. An illustrated identification key was provided for easy and accurate identification of adult of hairy caterpillars based on their morphological (male genitalial) characters. The study through a light on the existence of sexual dimorphism, polyphagous nature and diapause are the major hindrance in taxonomic identification. Hence, attempts were made to address these issues in the study.

Keywords: Erebidae, hairy caterpillars, male genitalia, taxonomy

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Authors: Martin Pumera

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Graphene materials are being widely used in electrochemistry due to their versatility and excellent properties as platforms for biosensing. Here we present current trends in the electrochemical biosensing of pesticides and other toxic compounds. We explore two fundamentally different designs, (i) using graphene and other 2-D nanomaterials as an electrochemical platform and (ii) using these nanomaterials in the laboratory on chip design, together with paramagnetic beads. More specifically: (i) We explore graphene as transducer platform with very good conductivity, large surface area, and fast heterogeneous electron transfer for the biosensing. We will present the comparison of these materials and of the immobilization techniques. (ii) We present use of the graphene in the laboratory on chip systems. Laboratory on the chip had a huge advantage due to small footprint, fast analysis times and sample handling. We will show the application of these systems for pesticide detection and detection of other toxic compounds.

Keywords: graphene, 2D nanomaterials, biosensing, chip design

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Authors: Moez Elsaadani, Noel Durand, Brice Sorli, Didier Montet

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Governments and international instances are trying to improve the food safety system to prevent, reduce or avoid the increase of food borne diseases. This food risk is one of the major concerns for the humanity. The contamination by mycotoxins is a threat to the health and life of humans and animals. One of the most common mycotoxin contaminating feed and foodstuffs is Ochratoxin A (OTA), which is a secondary metabolite, produced by Aspergillus and Penicillium strains. OTA has a chronic toxic effect and proved to be mutagenic, nephrotoxic, teratogenic, immunosuppressive, and carcinogenic. On the other side, because of their high stability, specificity, affinity, and their easy chemical synthesis, aptamer based methods are applied to OTA biosensing as alternative to traditional analytical technique. In this work, five aptamers have been tested to confirm qualitatively and quantitatively their binding with OTA. In the same time, three different analytical methods were tested and compared based on their ability to detect and quantify the OTA. The best protocol that was established to quantify free OTA from linked OTA involved an ultrafiltration method in green coffee solution with. OTA was quantified by HPLC-FLD to calculate the binding percentage of all five aptamers. One aptamer (The most effective with 87% binding with OTA) has been selected to be our biorecognition element to study its electrical response (variation of electrical properties) in the presence of OTA in order to be able to make a pairing with a radio frequency identification (RFID). This device, which is characterized by its low cost, speed, and a simple wireless information transmission, will implement the knowledge on the mycotoxins molecular sensors (aptamers), an electronic device that will link the information, the quantification and make it available to operators.

Keywords: aptamer, aptasensor, detection, Ochratoxin A

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Authors: Shimayali Kaushal, Nitesh Priyadarshi, Nitin Kumar Singhal

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Food borne bacterial species have been identified as major pathogens in most of the severe pathogen-related diseases among humans which result in great loss to human health and food industry. Conventional methods like plating and enzyme-linked immune sorbent assay (ELISA) are time-consuming, laborious and require specialized instruments. Nanotechnology has emerged as a great field in case of rapid detection of pathogens in recent years. The AuNRs material has good electro-optical properties due to its larger light absorption band and scattering in surface plasmon resonance wavelength regions. By exploiting the sugar-based adhesion properties of microorganism, we can use the glycoconjugates capped gold nanorods as a potential nanobiosensor to detect the foodborne pathogen. In the present study, polyethylene glycol (PEG) coated gold nanorods (AuNRs) were prepared and functionalized with different types of carbohydrates and further characterized by UV-Visible spectrophotometry, dynamic light scattering (DLS), transmission electron microscopy (TEM). The reactivity of above said nano-biosensor was probed by lectin binding assay and also by different strains of foodborne bacteria by using spectrophotometric and microscopic techniques. Due to the specific interaction of probe with foodborne bacteria (Escherichia coli, Pseudomonas aeruginosa), our nanoprobe has shown significant and selective ablation of targeted bacteria. Our findings suggest that our nanoprobe can be an ideal candidate for selective optical detection of food pathogens and can reduce loss to the food industry.

Keywords: glyco-conjugates, gold nanorods, nanobiosensor, nanoprobe

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Authors: Peng Hou

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Natural products produced from marine bacteria serve as an immense reservoir for anti-infective drugs and therapeutic agents. Nowadays, heterologous expression of gene clusters of interests has been widely adopted as an effective strategy for natural product discovery. Briefly, the heterologous expression flowchart would be: biosynthetic gene cluster identification, pathway construction and expression, and product detection. However, gene cluster capture using traditional Transformation-associated recombination (TAR) protocol is low-efficient (0.5% positive colony rate). To make things worse, most of these putative new natural products are only predicted by bioinformatics analysis such as antiSMASH, and their corresponding natural products biosynthetic pathways are either not expressed or expressed at very low levels under laboratory conditions. Those setbacks have inspired us to focus on seeking new technologies to efficiently edit and refractor of biosynthetic gene clusters. Recently, two cutting-edge techniques have attracted our attention - the CRISPR-Cas9 and Gibson Assembly. By now, we have tried to pretreat Brevibacillus laterosporus strain genomic DNA with CRISPR-Cas9 nucleases that specifically generated breaks near the gene cluster of interest. This trial resulted in an increase in the efficiency of gene cluster capture (9%). Moreover, using Gibson Assembly by adding/deleting certain operon and tailoring enzymes regardless of end compatibility, the silent construct (~80kb) has been successfully refactored into an active one, yielded a series of analogs expected. With the appearances of the novel molecular tools, we are confident to believe that development of a high throughput mature pipeline for DNA assembly, transformation, product isolation and identification would no longer be a daydream for marine natural product discovery.

Keywords: biosynthesis, CRISPR-Cas9, DNA assembly, refactor, TAR cloning

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Authors: Wei Ji

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This study was conducted in the Kansas City metropolitan area of the United States, which has experienced significant urban sprawling in recent decades. The remote sensing of land cover changes in this area spanned over four decades from 1972 through 2010. The project was implemented in two stages: the first stage focused on detection of long-term trends of urban land cover change, while the second one examined how to detect the coupled effects of human impact and climate change on urban landscapes. For the first-stage study, six Landsat images were used with a time interval of about five years for the period from 1972 through 2001. Four major land cover types, built-up land, forestland, non-forest vegetation land, and surface water, were mapped using supervised image classification techniques. The study found that over the three decades the built-up lands in the study area were more than doubled, which was mainly at the expense of non-forest vegetation lands. Surprisingly and interestingly, the area also saw a significant gain in surface water coverage. This observation raised questions: How have human activities and precipitation variation jointly impacted surface water cover during recent decades? How can we detect such coupled impacts through remote sensing analysis? These questions led to the second stage of the study, in which we designed and developed approaches to detecting fine-scale surface waters and analyzing coupled effects of human impact and precipitation variation on the waters. To effectively detect urban landscape changes that might be jointly shaped by precipitation variation, our study proposed “urban wetscapes” (loosely-defined urban wetlands) as a new indicator for remote sensing detection. The study examined whether urban wetscape dynamics was a sensitive indicator of the coupled effects of the two driving forces. To better detect this indicator, a rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. Three SPOT images for years 1992, 2008, and 2010, respectively were classified with this technique to generate the four types of land cover as described above. The spatial analyses of remotely-sensed wetscape changes were implemented at the scales of metropolitan, watershed, and sub-watershed, as well as based on the size of surface water bodies in order to accurately reveal urban wetscape change trends in relation to the driving forces. The study identified that urban wetscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds in response to human impacts at different scales. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while generally smaller wetlands decreased mainly due to human development activities. These results confirm that wetscape dynamics can effectively reveal the coupled effects of human impact and climate change on urban landscapes. As such, remote sensing of this indicator provides new insights into the relationships between urban land cover changes and driving forces.

Keywords: urban land cover, human impact, climate change, rule-based classification, across-scale analysis

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: Susana Aragoneses Garrido

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Every day, the roads are scenery of numerous accidents involving vehicles, producing thousands of deaths and serious injuries all over the world. Investigations have revealed that Human Factors (HF) are one of the main causes of road accidents in modern societies. Distracted driving (including external or internal aspects of the vehicle), which is considered as a human factor, is a serious and emergent risk to road safety. Consequently, a further analysis regarding this issue is essential due to its transcendence on today’s society. The objectives of this investigation are the detection and assessment of the HF in order to provide solutions (including a better vehicle design), which might mitigate road accidents. The methodology of the project is divided in different phases. First, a statistical analysis of public databases is provided between Spain and The UK. Second, data is classified in order to analyse the major causes involved in road accidents. Third, a simulation between different paths and vehicles is presented. The causes related to the HF are assessed by Failure Mode and Effects Analysis (FMEA). Fourth, different car models are evaluated using the Rapid Upper Body Assessment (RULA). Additionally, the JACK SIEMENS PLM tool is used with the intention of evaluating the Human Factor causes and providing the redesign of the vehicles. Finally, improvements in the car design are proposed with the intention of reducing the implication of HF in traffic accidents. The results from the statistical analysis, the simulations and the evaluations confirm that accidents are an important issue in today’s society, especially the accidents caused by HF resembling distractions. The results explore the reduction of external and internal HF through the global analysis risk of vehicle accidents. Moreover, the evaluation of the different car models using RULA method and the JACK SIEMENS PLM prove the importance of having a good regulation of the driver’s seat in order to avoid harmful postures and therefore distractions. For this reason, a car redesign is proposed for the driver to acquire the optimum position and consequently reducing the human factors in road accidents.

Keywords: analysis vehicles, asssesment, ergonomics, car redesign

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Authors: Long Zhang, Ian Hampson, Loretta O' Donnell

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Practitioners in various industries, especially in the finance industry that conventionally benefit from financial capital and resources, appear to be increasingly aware of the importance of human capital resources (HCR) after the 2008 Global Financial Crisis. Scholars from diverse fields have conducted extensive and fruitful research on HCR within their own disciplines. This review suggests that the mainstream of pure quantitative research alone is insufficient to provide precise or comprehensive understanding of HCR. The complex relationships and interactions in HCR call for more integrative and cross-disciplinary research to more holistically understand complex and intricate HCRs. The complex nature of HCR requires deep qualitative exploration based on in-depth data to capture the everydayness of organizational activities and to register its individuality and variety. Despite previous efforts, a systematic and holistic integration of HCR research among multiple disciplines is lacking. Using a retrospective analysis of articles published in the field of economics, finance and management, including psychology, human resources management (HRM), organizational behaviour (OB), industrial and organizational psychology (I-O psychology), organizational theory, and strategy literatures, this study summaries and compares the major perspectives, theories, and findings on HCR research. A careful examination of the progress of the debates of HCR definitions and measurements in distinct disciplines enables an identification of the limitations and gaps in existing research. It enables an analysis of the interplay of these concepts, as well as that of the related concepts of intellectual capital, social capital, and Chinese guanxi, and how they provide a broader perspective on the HCR-related influences on firms’ competitive advantage. The study also introduces the themes of Environmental, Social and Governance, or ESG based investing, as the burgeoning body of ESG studies illustrates the rising importance of human and non-financial capital in investment process. The ESG literature locates HCR into a broader research context of the value of non-financial capital in explaining firm performance. The study concludes with a discussion of new directions for future research that may help advance our knowledge of HCR.

Keywords: human capital resources, social capital, Chinese guanxi, human resources management

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Authors: Camilla Elphick, Graham Hole, Samuel Hutton, Graham Pike

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Pupil size has been found to change irrespective of luminosity, suggesting that it can be used to make inferences about cognitive processes, such as cognitive load. To see whether identifying a target requires a different cognitive load to rejecting distractors, the effect of viewing a target (compared with viewing distractors) on pupil size was investigated using a sequential video lineup procedure with two lineup sessions. Forty one participants were chosen randomly via the university. Pupil sizes were recorded when viewing pre target distractors and post target distractors and compared to pupil size when viewing the target. Overall, pupil size was significantly larger when viewing the target compared with viewing distractors. In the first session, pupil size changes were significantly different between participants who identified the target (Hits) and those who did not. Specifically, the pupil size of Hits reduced significantly after viewing the target (by 26%), suggesting that cognitive load reduced following identification. The pupil sizes of Misses (who made no identification) and False Alarms (who misidentified a distractor) did not reduce, suggesting that the cognitive load remained high in participants who failed to make the correct identification. In the second session, pupil sizes were smaller overall, suggesting that cognitive load was smaller in this session, and there was no significant difference between Hits, Misses and False Alarms. Furthermore, while the frequency of Hits increased, so did False Alarms. These two findings suggest that the benefits of including a second session remain uncertain, as the second session neither provided greater accuracy nor a reliable way to measure it. It is concluded that pupil size is a measure of face recognition strength in the first session of a target present lineup procedure. However, it is still not known whether cognitive load is an adequate explanation for this, or whether cognitive engagement might describe the effect more appropriately. If cognitive load and cognitive engagement can be teased apart with further investigation, this would have positive implications for understanding eyewitness identification. Nevertheless, this research has the potential to provide a tool for improving the reliability of lineup procedures.

Keywords: cognitive load, eyewitness identification, face recognition, pupillometry

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Authors: Najm Alotaibi

Abstract:

Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: human motion capture, computer vision, vision-based, tracking

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Authors: Mohamed Gaith, Zaid Haddadin, Abdulah Wahbe, Mahmoud Hamam, Mahmoud Qunees, Mohammad Al Khatib, Mohammad Bsaileh, Abd Al-Aziz Jaber, Ahmad Aqra’a

Abstract:

The crack is one of the most common types of failure in pipelines that convey fluid, and early detection of the crack may assist to avoid the piping system from experiencing catastrophic damage, which would otherwise be fatal. The influence of flow velocity and the presence of a crack on the performance of a tapered simply supported pipe containing moving fluid is explored using the finite element approach in this study. ANSYS software is used to simulate the pipe as Bernoulli's beam theory. In this paper, the fluctuation of natural frequencies and matching mode shapes for various scenarios owing to changes in fluid speed and the presence of damage is discussed in detail.

Keywords: damage detection, finite element, tapered pipe, vibration characteristics

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Authors: Mohammad Motiee

Abstract:

From Kierkegaard to Sartre, the concept of 'being' was debated over various angles in the philosophy of being. Then, the futility, nothingness and absurdity of human condition in the world were all justified and led to a kind of solution by different approaches like Christianity, loss of faith, authentic existence and responsibility. In an extreme concern, the human condition in the world was pondered in different ways and the philosophy of thought tried to render an awareness of such condition for human beings. The present study aims at illustration of some approaches presented by prominent existentialists to justify the controversies in the concept of existence in human life.

Keywords: existence, existentialism, alienation, being

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Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

Abstract:

The automated epileptic seizure detection research field has emerged in the recent years; this involves analyzing the Electroencephalogram (EEG) signals instead of the traditional visual inspection performed by expert neurologists. In this study, a Support Vector Machine (SVM) that uses Weighted Permutation Entropy (WPE) as the input feature is proposed for classifying normal and seizure EEG records. WPE is a modified statistical parameter of the permutation entropy (PE) that measures the complexity and irregularity of a time series. It incorporates both the mapped ordinal pattern of the time series and the information contained in the amplitude of its sample points. The proposed system utilizes the fact that entropy based measures for the EEG segments during epileptic seizure are lower than in normal EEG.

Keywords: electroencephalogram (EEG), epileptic seizure detection, weighted permutation entropy (WPE), support vector machine (SVM)

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Authors: Tamanda Kamwendo

Abstract:

The concept of benefit sharing has been a prominent global debate in the world, gaining traction in human research ethics. Despite its prevalence, the concept of benefit sharing is not without controversy over its meaning and justification. This is due to the fact that it lacks a broadly accepted definition and many proponents discuss benefit sharing by arguing for its necessity rather than engaging in critical intellectual engagement with technical issues such as what it implies. What is clear in the literature is that the underlying premise of benefit-sharing is that research involving underprivileged and marginalized people is currently unjust and inequitable because these people are denied access to these gains; thus, benefit-sharing arrangements are required for these research projects to be just and equitable. This paper, therefore, investigates the discourses and justifications behind the concept of benefit sharing to human participants, particularly when dealing with human genomics research. Furthermore, considering that benefit sharing is generally viewed as a transaction between research organizations and research participants, it raises ethical concerns concerning the commodification of human material and undermines the sanctity of the human genome. This is predicated on the idea that research sponsors would be compelled to deliver a minimum set of possible benefits to research participants and communities in exchange for their involvement in the study. There is, therefore, need to protect benefit-sharing practices in international health research by developing a governance legal framework. A legal framework of benefit sharing will also dispel the issue of commodification of human material where human genomic research is done.

Keywords: benefit sharing, human participants, human genomic research, ethical concerns

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Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

Abstract:

A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

Procedia PDF Downloads 746