Digital Manipulation Research Articles

Quantitative Characteristics of Groundwater and its Distribution in Tal-Afar Region- Iraq

The current research aims to know the quantitative characteristics of groundwater and its spatial distribution in Tal Afar district. It was relied on a set of data related to groundwater. All of them were entered into the GIS environment for the purpose of performing digital manipulations and drawing out maps. It was found that the depth of the groundwater ranges between (0-519) m, the stable groundwater level is within (0-89) m, and the variable groundwater level is (0-165) m. And the amount of decrease in the wells was within (0-146.4) m, and the productivity of these wells ranged between (37.28-0) L/sec, and the amount of conductivity was between (1345-0) m2 / day, and the productivity of water springs spread in the study area It was within (0-1000) L / sec. The study showed that the distribution and direction of the wells are from the northwest to the southeast of the study area and its standard distance covered 61.5% of the wells data, and the direction of the wells distribution was 120º towards the north in an oval shape that included approximately 66.76% of the data entered wells.

Digital Manipulation: Portraying the word Haram of smoking (Cigarette & e-Cigarette)

This paper explores the effectiveness of implementing image manipulation techniques and its capability to legitimize and portray the word Haram of smoking cigarettes and e-cigarettes, which was started in fatwa 1995 and 2015, through creative photography. It shows how creativity can be entrenched by adding the manipulation technique in photography and bringing different perspectives and directions to the viewers. The paper will define the ethics of implementing the manipulation technique in photography and study its requirements and impacts. It could help contrive anti-smoking advertisements that stated that smoking is Haram among Muslims. Keywords: Digital Manipulation, Fatwa Haram of Smoking, Cigarette, e-Cigarette eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7iSI7%20(Special%20Issue).3832

Upgrading the protection of children from manipulative and addictive strategies in online games


 
 
 Despite the increasing awareness from academia, civil society and media to the issue of child manipulation online, the current EU regulatory system fails at providing sufficient levels of protection. Given the universality of the issue, there is a need to combine and further these scattered efforts into a unitary, multidisciplinary theory of digital manipulation that identifies causes and effects, systematizes the technical and legal knowledge on manipulative and addictive tactics, and to find effective regulatory mechanisms to fill the legislative gaps. In this paper we discuss manipulative and exploitative strategies in the context of online games for children, suggest a number of possible reasons for the failure of the applicable regulatory system, propose an “upgrade" for the regulatory approach to address these risks from the perspective of freedom of thought, and present and discuss technological approaches that allow for the development of games that verifiably protect the privacy and freedoms of players.
 
 

Efecto del proceso de equilibrio en espermatozoides caninos después de la vitrificación con dilutor a base de agua de coco con adición de lecitina de soya y sacarosa como crioprotectores no permeables

The aim of the present study was to evaluate the effect of equilibration process on canine sperms after vitrification using coconut water extender with addition of soy lecithin and sucrose as nonpermeable cryoprotectants. Twelve ejaculates were collected separately by digital manipulation from 12 adult dogs. Only the second fraction of the ejaculate was used in this study, which was evaluated about volume, concetration, viability, total and progressive motility, kinetic parameters and morphology. After evaluation, semen was diluted with a coconut water extender (50% coconut water (v/v), 25% (v/v) distilled water and 25% (v/v) 5% anhydrous monosodium citrate solution) with addition of soy lecithin and fructose at 1% (v/v) and 0.25 M sucrose until final concentration of 100x106 spermatozoa/ml. Samples were divided into three aliquots and each of them was processed at different regimens: without equilibration, 5ºC for 30 minutes and 5ºC for 60 minutes and then vitrified by dropping 30 μl of sperm suspension directly into liquid nitrogen. Sperm pellets were devitrified at least one week later as three of them were dropped into 0.3 mL of CaniPlus AI (Minitüb, Germany), which was previously warmed in a water bath at 37ºC for 2 minutes. Sperm concentration and motility parameters were assayed using a computer-aided sperm analysis (CASA) system, viability-by supravital staining technique and morphology parameters were evaluated in Haemacolor® stained semen samples. In conclusion, our results demonstrate that when vitrification and coconut water extender with addition of 1% soy lecithin and 0.25 M sucrose as cryoprotectants were used, presence of equilibration time of 60 minutes returned the best canine sperm quality results.

Dual-Energy, Dual-Exposure PA and Lateral Chest Radiograph: Not Your Father's Chest X-Ray.

In the last two decades, our military and federal health care facilities have transitioned from traditional X-rays exposing film screen systems, developed much like photographic film, to an entirely digital detection system that affords computer processing of images and digital image and report distribution. While health care providers are well aware of the practicality of these advancements, they may not be aware of the improved diagnostic capabilities afforded by these new methods. In this report, we outline how application of physical principles of X-rays, with digital detectors and computer data manipulation, can present images demonstrating chest and heart diseases that were previously not readily visible by traditional film screen systems. More recently, dual-energy, dual-exposure systems have been implemented. This commentary is to educate the medical community so that they may better understand not only the written report but the information on the images being provided, along with potential pitfalls to avoid. Specifically, we demonstrate improved detection of pulmonary nodules and coronary atherosclerosis with the dual-energy technique.

EFFICACY OF DIGITAL MANIPULATION OF THYROID CARTILAGE, FLUENCY SHAPING THERAPY AND COMBINATION OF BOTH IN TREATMENT OF STUTTERING SEVERITY: A RANDOMIZED CLINICAL TRIAL

Background: The stuttering is manifested by disruption in normal speech flow and fluency that also disturbs social and emotional wellbeing. There is immediate need of rehabilitation for the improvement of fluency and reduce the severity of stuttering.Objective:To compare the digital manipulation of thyroid cartilage (DMTC), fluency shaping therapy (FST) and combination of DMTC and FST for improving severity in stuttering patients. Material and Method: A randomized clinical trial was conducted at National Institute of Rehabilitation Medicine. The patients were enrolled through non-probability, convenient sampling technique. The participants were randomly allocated into three equal groups (n=10): DMTC group, FST group and combination of both. The Scale of Rating Severity of Stuttering (SRSS) was used to assess the severity level at baseline, 2ndweek, 4thweek, 8thweek and 12thweek of intervention.Results: The mean age of DMTC, FST and combination group was, 22.25 ±3.33 years, 21.65±3.36 and 21.35±3.76 years respectively. Friedman with post hoc test revealed significant improvement (p<0.05) in all groups but combination group had showed better outcome than single DMTC and FST intervention. A Kruskal-Wallis H test showed that there was no significant difference (p≥0.05) among DMTC, FST and Combination group from baseline to 8thweeks of training, but significant difference {X2(2) =5.897, p<0.014} was observed after 12thweek of training among the groups. The post hoc test showed that the combination group was more significantly improved as compared to DMTC group {MR=9.10 ver. MR=17.71, p=0.012} but not significant difference between difference between combination and FST group (p=0.317) as well as DMTC and FST group (p=0.619) regarding severity of stuttering. Conclusion: It is concluded that combination of digital manipulation of thyroid cartilage and fluency shaping therapy were more beneficial for improving fluency in stuttering patients. Key words:Digital manipulationtherapy,fluency shaping therapy, stammering, stuttering.

Design of Semiautomatic Digital Creation System for Electronic Music Based on Recurrent Neural Network.

Semiautomated digital creation is increasingly important in the manipulation of electronic music. How to realize the learning of local effective features of audio data is a difficult point in the current research field. Based on recurrent neural network theory, this paper designs a semiautomatic digital creation system for electronic music for digital manipulation and genre classification. The recurrent neural network improves the transmission of electronic music information between the input and output of the network by adopting dense connections consistent with DenseNet and adopts an inception-like structure for the autonomous selection of effective recursive nuclear electronic music categories. In the simulation process, the prediction method based on semiautomatic digital audio clips is also adopted, which pays more attention to the learning of local effective features of audio data, which gives the model the ability to create audio samples of different lengths and improves the model's support for creative tasks in different scenarios. It includes the determination of the number of neurons, the selection of the function of neurons, the determination of the connection method, and the specific learning algorithm rules, and then the training samples are formed. The experimental results show that the recurrent neural network exhibits powerful feature extraction ability and classification ability of music information. The 10-fold cross-validation on GTZAN dataset and ISMIR2004 dataset has obtained 88.7% and 87.68%, surpassing similar ones. The model has reached a leading level. After further use of the MSD (Million Song Dataset) dataset for pre-semiautomatic training, the model effect has been further greatly improved. The accuracy rate on the dataset has been increased to 91.0% and 89.91%, respectively, which has improved the semiautomatic number and creative advancement.

Perception of Smile Aesthetics and Attractiveness among Saudi Females

Smile aesthetic, known as the static and dynamic relationship of the dentition and supporting structures to the facial soft tissues, is one of the most important elements of facial attractiveness. The objective of the study was to assess the perception of smile aesthetics and attractiveness through digital image manipulation of aesthetic variables and to compare those perceptions according to diverse sociodemographic data among female Saudi laypeople attending the dental clinic. A crosssectional study of 193 female Saudi participants were randomly selected and consented to answer the study questionnaire. Nine smile photograph images were created to compare different smile aesthetic perceptions. Two groups were recruited: 120 participants in the first group (under 30 years old) and 73 participants in the second group (30 years old or above). All participants in both groups were asked to choose the attractiveness of each smile image using multiple-choice options. A statistically significant finding showed that normal buccal corridors were chosen as the most attractive smile by 42.5% of the participants in the younger group and by a significantly higher ratio of the participants with a bachelor’s degree or higher level of education at 49% (p < 0.05). Laypeople’s preferences regarding smile attractiveness vary, but a normal appearance was the ideal choice for the majority. Orthodontic treatment should consider the general sociocultural understanding of smile perception.

Feature compensation network based on non-uniform quantization of channels for digital image global manipulation forensics

With the popularity of image editing software and technology, it has become very easy to manipulate an image, which has challenged the authenticity and security of digital images. Digital Image Manipulation Forensics (DIMF) has become an important research direction to confirm the authenticity of images, detect the manipulations that images have undergone, and avoid the misuse of image editing. Currently, most DIMF targets the detection of multiple image manipulations with fixed parameters. However, we consider detecting image manipulation in a more complex scenario where the parameters are chosen to be arbitrary. In this paper, we propose a Feature Compensation Network (FCNet) based on non-uniform quantization of channels. Briefly, it contains three important parts: (1) feature enhancement block, which extracts and enhances valid information from low-level features and eliminates semantic gaps between them and the high-level features. (2) sensitivity estimation block, which obtains the importance coefficients of each channel and guides the non-uniform quantization of low-level features. (3) adaptive average pooling, which keeps the resolution of low-level features and high-level features consistent and ensures that subsequent feature fusion is appropriate. Through extensive experiments, we have demonstrated the effectiveness of the proposed method in detecting multiple image manipulations.

A Review of Image Processing Techniques for Deepfakes.

Deep learning is used to address a wide range of challenging issues including large data analysis, image processing, object detection, and autonomous control. In the same way, deep learning techniques are also used to develop software and techniques that pose a danger to privacy, democracy, and national security. Fake content in the form of images and videos using digital manipulation with artificial intelligence (AI) approaches has become widespread during the past few years. Deepfakes, in the form of audio, images, and videos, have become a major concern during the past few years. Complemented by artificial intelligence, deepfakes swap the face of one person with the other and generate hyper-realistic videos. Accompanying the speed of social media, deepfakes can immediately reach millions of people and can be very dangerous to make fake news, hoaxes, and fraud. Besides the well-known movie stars, politicians have been victims of deepfakes in the past, especially US presidents Barak Obama and Donald Trump, however, the public at large can be the target of deepfakes. To overcome the challenge of deepfake identification and mitigate its impact, large efforts have been carried out to devise novel methods to detect face manipulation. This study also discusses how to counter the threats from deepfake technology and alleviate its impact. The outcomes recommend that despite a serious threat to society, business, and political institutions, they can be combated through appropriate policies, regulation, individual actions, training, and education. In addition, the evolution of technology is desired for deepfake identification, content authentication, and deepfake prevention. Different studies have performed deepfake detection using machine learning and deep learning techniques such as support vector machine, random forest, multilayer perceptron, k-nearest neighbors, convolutional neural networks with and without long short-term memory, and other similar models. This study aims to highlight the recent research in deepfake images and video detection, such as deepfake creation, various detection algorithms on self-made datasets, and existing benchmark datasets.

Detection of image manipulation with convolutional neural network and local feature descriptors

In recent times, numerous digital image manipulation detection approaches have been proposed to detect which processing operations were applied to manipulate digital images. Most of these approaches consider the situation in which an image is manipulated by only one manipulation operation. However, practical image manipulation often involves multiple manipulation operations. It is important to detect multiple image manipulation operations and the order in which they were applied to establish the origin and genuineness of a given image as well as the processing history it has gone through. In this article, we proposed a new method to determine multiple image processing operation and operation chains based on convolutional neural network (CNN) and local optimal oriented pattern (LOOP). The proposed method is based on CNN and LOOP in which CNN extracts and learns image manipulation traces from the LOOP maps of the input images that are classified using softmax, extra-tree, and extreme gradient boosting (XGBOOST) classifiers. Detailed experiments show that the proposed model can attain overall detection accuracies of 99.81% and 99.15% in identifying different image manipulations and manipulation operation chains, respectively

Perceptual Mapping-Based Image Tamper Detection and Recovery Algorithm

The importance of digital image authentication has grown in the last decade particularly with the widespread availability of digital media and image manipulation tools. As a result, different techniques were developed to detect fraudulent alterations in digital images and restore the original data. In this paper, a new algorithm is proposed to authenticate images by hiding a copy of the approximation band in the original image. The approximation band is hidden by embedding it inside the image pixels. The intensity of the hiding was decided using a perceptual map that simulates the human vision system and adds more intensity in areas where the human eye cannot recognize changes. The perceptual map consists of three parts, luminance mask, texture mask, and edge detection mask. Results show a high ability to blindly recover images after different attacks such as removing and blocking attacks. At the same time, the structure similarity index of resultant images was higher than 0.99 for all tested images.

Discovering ancient cave art using 3D photogrammetry: pre-contact Native American mud glyphs from 19thUnnamed Cave, Alabama

Since 1979, when the first cave art was documented in North America, dozens of other examples have come to light. Among these, 19thUnnamed Cave in Alabama contains hundreds of pre-contact Native American mud glyph drawings. In 2017, 3D modelling of the glyphs was initiated, ultimately enabling digital manipulation of the chamber space and revealing images that could not be perceived prior to modelling. Most surprisingly, the cave's ceiling features very large anthropomorphic glyphs that are not apparentin situdue to the tight confines of the cave. We argue that photogrammetry offers untapped potential for not simply the documentation but also the discovery of a variety of archaeological phenomena.

Semen Collection, Cryopreservation and Artificial Insemination in Dogs

Today, the methods of artificial insemination, that have recently become a biotechnological phenomenon, have being used in dogs especially for those partners that are largely unable to mate because of differences in their body sizes. Artificial insemination is likely only by diluting the semen collected in order to protect it from the environmental conditions, by using some short- and long-term preservation methods and by transferring it into the females with proper techniques. Therefore, in this brief review, some data about the approach to the male at the time of semen collection, as well as the collection itself (digital manipulation, conic plastic rubber along with hand massage, and electrical stimulations (the electro-ejeculator)), dilution (Tes, Bes, Hepes, Pipes, Tris, Tes/Tris and commercial extenders, at 1:1-1:5 dilution rate), short (at +4 oC) - and long-term (in ampoule, pellet and straw) frozen storage (within liquid nitrogen, at -196 oC) of semen and artificial insemination methods (intravaginal catheter, Norwegian intrauterine catheter, endoscopic intrauterine and surgical intrauterine technique)) are given in dogs.

There and back again: how target market determination obligations for financial products may incentivise consumer data profiling

ABSTRACT Increasingly precise data profiling of consumers is one of the drivers of profit for the financial industry in the digital age. However, data profiling may also bring about harm to consumers, ranging from data breaches to unfair pricing, digital manipulation, discrimination and exclusion of vulnerable consumers, which is particularly problematic in financial services context due to the consequences it has on consumers’ access to financial products. The focus of this article are target market determination (TMD) obligations for financial products and their interplay with data protection rules. It asks if financial product governance rules, requiring TMD and distribution of products within the target market, may further incentivise data profiling of consumers by financial services providers. I analyse this issue looking at two sets of rules applicable to financial firms in Australia: (1) the new financial products governance rules, which came into force in October 2021, and (2) the data protection rules: Australian Privacy Act 1988 and the GDPR. If these frameworks fail to strike a balance between (surprisingly) competing interests of consumer protection regarding the provision of appropriate financial products and the use of consumers’ data in digital profiling, the new rules may backfire, resulting in unintended consumer harms.

SCOPE and EaaSI: Software Emulation and the Future of Architectural History

SCOPE and EaaSI: Software Emulation and the Future of Architectural History

EFFECT OF DIGITAL DISTRUST ON ATTITUDE TOWARDS ONLINE SHOPPING AMONG UNDERGRADUATES IN ENUGU STATE, NIGERIA

There is a growing trend in online shopping in Nigeria fuelled mainly by the increasing innovations in cyberspace. However, the consumers unrestrained passion for the digital marketplace has been influenced by concerns about security, privacy, data breach, and trust. Consumers are becoming increasingly aware of the presence of digital manipulations. Thus, the present study examines the effect of digital distrust on attitude towards online shopping. Two hundred and twenty-eight undergraduates from three public tertiary institutions in Enugu state participated in the study. The respondents completed a self-report measure of digital distrust and attitude towards online shopping. The simple regression analysis revealed that digital distrust is a positive predictor of online shopping. The implications of the study are discussed.

Body-kun/body-chan style model figures for artists in forensic visualization applications

Posture and body position are often in the focus of forensic medicine. Visualization for the purposes of documentation, teaching, scientific presentation or expert opinion in court is often desired. Plenty of possible tools to support visualization are available. However, there is a significant gap between quick drawings and more complex techniques. Body-chan (female) and body-kun (male) artist’s model figurines (genericized trademark) may provide a useful means to fill this gap. These models, about 12–15 cm in height, are multi-articulated humanoids of realistic proportions, intended to serve as models for manga (japanese comic) drawing. Plenty of different models are available in different quality which usually are equipped with interchangeable hand and feet attachments, a frame for ‘levitating’ positions as well as assorted objects to scale. These inexpensive models may be positioned quickly and intuitively. Photodocumentation from various angles can be performed using a mobile phone camera. Images may be further improved applying digital image manipulation software. Taken together, the process is quick and intuitive and the level of achievable complexity is sufficient for many forensic applications.

Stabilizing a supervised bot detection algorithm: How much data is needed for consistent predictions?

Social media bots have been characterized in their use in digital activism and information manipulation, due to their roles in information diffusion. The detection of bots has been a major task within the field of social media computation, and many datasets and bot detection algorithms have been developed. With these algorithms, the bot score stability is key in estimating the impact of bots on the diffusion of information. Within several experiments on Twitter agents, we quantify the amount of data required for consistent bot predictions and analyze agent bot classification behavior. Through this study, we developed a methodology to establish parameters for stabilizing the bot probability score through threshold, temporal and volume analysis, eventually quantifying suitable threshold values for bot classification (i.e. whether the agent is a bot or not) and reasonable data collection size (i.e. number of days of tweets or number of tweets) for stable scores and bot classification.

Digital collaboratory

ABSTRACT Storying their work with educators and young children at a Canadian early years learning centre, the co-authors puzzle over the means, affects and embodiments of digital collaboratories, proposing the latter as spaces of chimeric organic and non-organic configurations. This exploratory and experimental piece draws out opportunities for thinking complexly about the everyday encounters with the digital in early childhood education. In following the circulation of human and more-than-human digital/material events, the compositions of Franken-Tree and Franken-Sound are used to trace how common everyday interactions with digital are implicated in the enactment of pedagogical practices and, more broadly, in the making of place. Within spaces of early childhood classrooms, digital manipulations allow for multiple place-events to unravel in a non-linear enmeshing of outside and inside, of here and somewhere, of now, then and who-knows-when. Because digital enters childhood spaces with ease, educators are compelled to consider both its transgressive possibilities and disciplining powers, and to question the seemingly endless ability of algorithms to hide the layers of damage behind the layers of saturated surfaces.