Search results for: mobile image retrieval

Authors: Vidyarini Dwita, Rebecca Fanany

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This study will discuss the growth of the market for smartphone technology in Indonesia. This country, with the world’s fourth largest population, has a reputation as the social media capital of the world, and this reputation is largely justified. The penetration of social media is high in Indonesia which has one of the largest global markets. Most Indonesian users of Facebook, Twitter and other social media platforms access the sites from their mobile phones. Indonesia is expected to continue to be a major market for digital mobile devices, such as smartphone and tablets that can access the internet. The aim of this study to describe the way responses of Indonesian consumers to smartphone advertising using English and Indonesian will impact on their perceptions of the prestige and product image of the advertised items and thus influence consumer intention to purchase the item. Advertising for smartphones and similar products is intense and dynamic and often draws on the social attitudes of Indonesians with respect to linguistic and cultural content and especially appeals to their desire to be part of global mainstream culture. The study uses a qualitative method based on in-depth interviews with 30 participants. Content analysis is employed to analyse the responses of Indonesian consumers to smartphone advertising that uses English and Indonesian text. Its findings indicate that consumers’ impressions of English and Indonesian slogans influence their attitudes toward smartphones, suggesting that linguistic context plays a role in influencing consumer purchases.

Keywords: consumer purchases, marketing communication, product image, smartphone advertising, sociolinguistic

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Authors: Vivek Kumar Singh, Tripti Singh

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An ad hoc wireless network consists of mobile networks which creates an underlying architecture for communication without the help of traditional fixed-position routers. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol used for Mobile Ad hoc Network (MANET). Nevertheless, the architecture must maintain communication routes although the hosts are mobile and they have limited transmission range. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks, so that MANET requires different protocols. This paper presents the performance analysis of the routing protocols used various parameter-patterns with Two-ray model.

Keywords: AODV, packet transmission rate, pause time, ZRP, QualNet 6.1

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Authors: Y. Kong, I. Masud, M. H. Nyaso

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This paper seeks to examine consumers’ intention to adopt and use mobile payment method in Ghana. A conceptual framework was adopted from the extant literature using the Technology Acceptance Model (TAM) and the Theory of Reasoned Action (TRA) as the theoretical bases. Data for the study was obtained from a sample of 425 respondents through online and direct surveys using structured questionnaire. Structural Equation Modeling was used to analyse the data through SPSS v.22 and SmartPLS v.3. Findings with regards to the determinants of mobile payment system adoption indicate that subjective norm, perceived ease of use, attitude, and perceived usefulness play active roles in consumers’ decision to adopt mobile payment system in Ghana. Also, perceived usefulness and perceived ease of use have a significant and positive influence on consumers’ attitude towards mobile payment adoption in Ghana. Further, subjective norm was found to influence perceived usefulness and perceived ease of use of mobile payment adoption in Ghana. The study contributes to literature on mobile payment system from developing country context. The study proffered some recommendations.

Keywords: consumer behaviour, mobile payment, subjective norm, theory of planned behavior

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Fathi Alwafie

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In this paper we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wide-band characteristics of the channel: Root Mean Square (RMS) delay spread characteristics and mean excess delay, is also investigated.

Keywords: propagation, ray tracing, network, mobile computing

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Sung Un Kim, Ivana Martinović, Snježana Stanarević Katavić

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As more and more youth use mobile devices, such as tablets and smartphones, for information seeking in their everyday lives, the purpose of this study is to understand the behaviors of youth seeking health information on mobile devices. The specific objective of this study is to examine 1) for what health issues youth use mobile devices, 2) for what reasons youth use mobile devices to obtain health information, 3) in what ways youth use mobile devices for health information, and 4) the features of health applications that youth find useful. The researchers devised a questionnaire for this study. Four hundred eight students from two high schools, located in Osijek, Croatia, participated by answering the questionnaire (281 girls and 127 boys). The collected data were analyzed using descriptive statistics and content analysis. The results show that among all participants, about 85 percent (n = 344) reported having used mobile devices for health information. The most frequent health topic for which they had been using mobile devices is physical activity (n = 273), followed by eating issues and nutrition (n = 224), mental health (n = 160), sexual health (n = 157), alcohol, drugs, and tobacco (n = 125), safety (n = 96) and particular diseases (n = 62). They use mobile devices to obtain health information due to the ease of use (n = 342), the ease of sharing health information (n = 281), portability (n = 215), timeliness (n = 162), and the ease of tracking/recording/monitoring health status (n = 147). Of those who have used mobile devices for health information, three-quarters (n = 261) use mobile devices to search health information, while 32.8% (n =113) use applications and 31.7% (n =109) browse information. Those who have used applications for health information (n = 113) consider the alert feature (n=107) as the most useful, followed by the tracking/recording/monitoring feature (n =92), the customized information feature (n = 86), the video feature (n = 58), and the sharing feature (n =39). It is notable that although health applications have been actively developed and studied, a majority of the participants search for or browse information on mobile devices, instead of using applications. The researchers will discuss reasons that some of them did not use mobile devices to obtain health information, students’ concerns about using health applications, and features that they wish to have in health applications.

Keywords: Croatia, health information, information seeking behaviors, mobile devices, youth

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Authors: Ahmed Deen

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The introduction of the mobile devices which were equipped with internet access and a camera, as well as the messaging services, has become a major inspiration for the use of the mobile devices in the growth in the reporting of news. Mobile journalism (MOJO) was a creation of modern technology, especially the use of mobile technology for video journalism purposes. MOJO, thus, is the process by which information is collected and disseminated to society, through the use of mobile technology, and even the use of the tablets. This paper seeks to better understand the ethics of Saudi mobile journalists towards news coverage. Also, this study aims to explore the relationship between minimizing harms and truth-seeking efforts among Saudi mobile journalists. Three main ethics were targeted in this study, which are seek truth and report it, minimize harm, and being accountable. Diffusion of innovation theory applied to reach this study’s goals. The non- probability sampling approach, ‘Snowball Sampling’ was used to target 124 survey participants, an online survey via SurveyMonkey that was distributed through social media platforms as a web link. The code of ethics of the Society of Professional Journalists has applied as a scale in this study. This study found that the relationship between minimizing harm and truth-seeking efforts is significantly moderate among Saudi mobile journalists. Also, it is found that the level journalistic experiences and using smartphones to cover news are weakly and negatively related to the perceptions of mobile journalism among Saudi journalists, while Saudi journalists who use their smartphone to cover the news between 1-3 years, were the majority of participants (55 participants by 51.4%).

Keywords: mobile journalism, Saudi journalism, smartphone, Saudi Arabia

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Authors: Jinming Ma, Tianbing Xia, Janusz Getta

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This paper presents the application of fuzzy set theory to implement of mobile advertisement anti-fraud systems. Mobile anti-fraud is a method aiming to identify mobile advertisement fraudsters. One of the main problems of mobile anti-fraud is the lack of evidence to prove a user to be a fraudster. In this paper, we implement an application by using fuzzy set theory to demonstrate how to detect cheaters. The advantage of our method is that the hardship in detecting fraudsters in small data samples has been avoided. We achieved this by giving each user a suspicious degree showing how likely the user is cheating and decide whether a group of users (like all users of a certain APP) together to be fraudsters according to the average suspicious degree. This makes the process more accurate as the data of a single user is too small to be predictable.

Keywords: mobile internet, advertisement, anti-fraud, fuzzy set theory

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Sankalp Devanand, Prateek Agasimani, Shamith V. S., Rohith Neeraje

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Machine translation has witnessed significant advancements in recent years, but the translation of languages with distinct linguistic characteristics, such as English and Sanskrit, remains a challenging task. This research presents the development of a dedicated English-to-Sanskrit machine translation model, aiming to bridge the linguistic and cultural gap between these two languages. Using a variety of natural language processing (NLP) approaches, including FastText embeddings, this research proposes a thorough method to improve word meaning retrieval. Data preparation, part-of-speech tagging, dictionary searches, and transliteration are all included in the methodology. The study also addresses the implementation of an interpreter pattern and uses a word similarity task to assess the quality of word embeddings. The experimental outcomes show how the suggested approach may be used to enhance word meaning retrieval tasks with greater efficacy, accuracy, and adaptability. Evaluation of the model's performance is conducted through rigorous testing, comparing its output against existing machine translation systems. The assessment includes quantitative metrics such as BLEU scores, METEOR scores, Jaccard Similarity, etc.

Keywords: machine translation, English to Sanskrit, natural language processing, word meaning retrieval, fastText embeddings

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

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Authors: Marylene S. Eder

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Existing location based alarm applications has inability to give information to user’s particular direction to a specified place of destination and does not display a particular scenic spot from its current location going to the destination. With this problem, a location based alarm mobile reminder was developed. The application is implemented on Android based smart phones to provide services like providing routing information, helping to find nearby hotels, restaurants and scenic spots and offer many advantages to the mobile users to retrieve the information about their current location and process that data to get more useful information near to their location. It reminds the user about the location when the user enters some predefined location. All the user needs to have is the mobile phone with android platform with version 4.0 and above, and then the user can select the destination and find the destination on the application. The main objective of the project is to develop a location based application that provides tourists with real time information for scenic spots and provides alarm to a specified place of destination. This mobile application service will act as assistance for the frequent travelers to visit new places around the City.

Keywords: location based alarm, mobile application, mobile reminder, tourist’s spots

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Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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Authors: Sulaiman Almutairy, Trevor Davies, Yota Dimitriadi

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This paper presents study investigating how to understand better the psychological readiness for mobile learning (m-learning) among Saudi students, while also evaluating m-learning in Saudi Arabia-a topic that has not yet received adequate attention from researchers. Data was acquired through a questionnaire administered to 131 Saudi students at UK universities, in July 2013. The study confirmed that students are confident using mobile devices in their daily lives and that they would welcome more opportunities for mobile learning. The findings indicated that Saudi higher education students are highly familiar with, and are psychologically ready for, m-learning.

Keywords: m-learning, mobile technologies, psychological readiness, higher education

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Authors: Muna Al-Siyabi

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When students bring mobile devices into the classrooms, they are frequently viewed as distractions from their daily educational practices rather than developing the twenty-first century skills. Such skills may involve sorting and extracting information, solving problems and evaluating results. Mobile devices, such as smartphones and tablets, have great potential for learning. Currently, schools and universities are embracing these devices with the aim of enhancing education. In Oman, mobile technologies have been introduced in the last ten years in two private schools to keep pace with the technological advancement. The researcher set out to examine the benefits and challenges of employing mobile learning in these two schools with the aim to inform the implementation of mobile technologies in more schools in Oman. The total of 16 teachers and 237 students responded to questionnaires, and 7 teachers and three student focus groups (of 13 students) were involved in interviews to explore how mobile technologies are used in these two schools. The questionnaires indicated that 87.5% of the sample teachers considered mobile learning helpful for learning and teaching. The teachers believed that mobile learning could promote learning, help teaching, offer vast resources, motivate students and save lesson time. Moreover, interviews with the teachers showed that mobile learning could offer several benefits like immediacy, saving lesson time, supporting differentiation, opportunities to learn anywhere, showing understanding, and offering vast resources. Most of the sample were also facing technical and classroom management challenges when employing mobile technologies in their lessons. In the interviews, most teachers complained of the difficulty to control their classes when they had mobile devices, which distracted their attention and understanding. They reported that their students were distracted by games and they needed to be trained to use mobile technologies for educational purposes. Most teachers recommended that certain parameters or restrictions should be established in any mobile learning project that restrict the usage of mobile technologies to educational purposes. In addition, teachers also emphasised that students needed to be trained on the advantages and limitations of mobile technologies. Teachers were also recommending that pedagogical training for using mobile technologies should be considered when implementing mobile learning in schools. These findings reveal that although of the challenges of managing their classes, teachers believe that mobile learning has great potential for learning. These results imply that mobile learning can be effectively implemented in school in Oman if certain factors and restrictions are considered.

Keywords: effective implementation, challenges, mobile learning, opportunities

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Authors: Bulelani Ngamntwini, Liezel Cilliers

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South Africa has one of the highest prevalence of obese people on the African continent. Forty-six percent of the adults in South Africa are physically inactive. Fitness applications can be used to increase physical inactivity. However, the uptake of mobile fitness applications in South Africa has been found to be poor due to usability challenges with the technology. The study developed a usability framework to influence the intention to use mobile fitness applications in South Africa. The study made use of a positivistic approach to collect data. A questionnaire was used to collect quantitative data from 377 respondents that have used mobile fitness applications in the past. A response rate of 80.90% was recorded. To analyse the data, the Pearson correlation was used to determine the relationships between the various hypotheses. There are four usability factors, efficiency, effectiveness, satisfaction, and learnability, which contribute to the intention of users to make use of mobile fitness applications. The study, therefore, recommends that for a mobile fitness application to be successful, these four factors must be considered and incorporated by developers when designing the applications.

Keywords: obese, overweight, physical inactivity, mobile fitness application, usability factors

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Authors: B. Madhevan, R. Sakkaravarthi, R. Diya

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The number and variety of mobile robot applications are increasing day by day, both in an industry and in our daily lives. First developed as a tool, nowadays mobile robots can be integrated as an entity in Internet-accessible resources. The present work is organized around four potential resources such as cloud computing, Internet of things, Big data analysis and Co-simulation. Further, the focus relies on integrating, analyzing and discussing the need for integrating Internet-accessible resources and the challenges deriving from such integration, and how these issues have been tackled. Hence, the research work investigates the concepts of the Internet-accessible resources from the aspect of the autonomous mobile robots with an overview of the performances of the currently available database systems. IaR is a world-wide network of interconnected objects, can be considered an evolutionary process in mobile robots. IaR constitutes an integral part of future Internet with data analysis, consisting of both physical and virtual things.

Keywords: internet-accessible resources, cloud computing, big data analysis, internet of things, mobile robot

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Authors: Abolfazl Mohammadijoo

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In this paper, we are investigating the sliding mode control approach for trajectory tracking of a two-link-manipulator with a wheeled mobile robot in its base. The main challenge of this work is the dynamic interaction between mobile base and manipulator, which makes trajectory tracking more difficult than n-link manipulators with a fixed base. Another challenging part of this work is to avoid from chattering phenomenon of sliding mode control that makes lots of damages for actuators in real industrial cases. The results show the effectiveness of the sliding mode control approach for the desired trajectory.

Keywords: mobile manipulator, sliding mode control, dynamic interaction, mobile robotics

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Authors: Eman A. Al-Hilo, Hawraa H. Al-Waelly

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In this work, fractal compression (FIC) technique is introduced based on using moment features to block indexing the zero-mean range-domain blocks. The moment features have been used to speed up the IFS-matching stage. Its moments ratio descriptor is used to filter the domain blocks and keep only the blocks that are suitable to be IFS matched with tested range block. The results of tests conducted on Lena picture and Cat picture (256 pixels, resolution 24 bits/pixel) image showed a minimum encoding time (0.89 sec for Lena image and 0.78 of Cat image) with appropriate PSNR (30.01dB for Lena image and 29.8 of Cat image). The reduction in ET is about 12% for Lena and 67% for Cat image.

Keywords: fractal gray level image, fractal compression technique, iterated function system, moments feature, zero-mean range-domain block

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Authors: Anu Malhotra

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An Ad-hoc network is one that is an autonomous, self configuring network made up of mobile nodes connected via wireless links. Ad-hoc networks often consist of nodes, mobile hosts (MH) or mobile stations (MS, also serving as routers) connected by wireless links. Different routing protocols are used for data transmission in between the nodes in an adhoc network. In this paper two protocols (OLSR and AODV) are analyzed on the basis of two parameters i.e. time delay and throughput with different data rates. On the basis of these analysis, we observed that with same data rate, AODV protocol is having more time delay than the OLSR protocol whereas throughput for the OLSR protocol is less compared to the AODV protocol.

Keywords: routing adhoc, mobile hosts, mobile stations, OLSR protocol, AODV protocol

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Authors: Gurinder Singh, Kulbir Singh

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Digital multimedia contents such as image, video, and audio can be tampered easily due to the availability of powerful editing softwares. Multimedia forensics is devoted to analyze these contents by using various digital forensic techniques in order to validate their authenticity. Digital image forensics is dedicated to investigate the reliability of digital images by analyzing the integrity of data and by reconstructing the historical information of an image related to its acquisition phase. In this paper, a survey is carried out on the forgery detection by considering the most recent and promising digital image forensic techniques.

Keywords: Computer Forensics, Multimedia Forensics, Image Ballistics, Camera Source Identification, Forgery Detection

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: R. K. Pateriya, Jyoti Bharti

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This paper presents an approach for data hiding methods which provides a secret communication between sender and receiver. The data is hidden in gray-scale images and the boundary of gray-scale image is used to store the mapping information. In this an approach data is in ASCII format and the mapping is in between ASCII value of hidden message and pixel value of cover image, since pixel value of an image as well as ASCII value is in range of 0 to 255 and this mapping information is occupying only 1 bit per character of hidden message as compared to 8 bit per character thus maintaining good quality of stego image.

Keywords: ASCII value, cover image, PSNR, pixel value, stego image, secret message

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Chih-Ping Chen

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Despite the increasing popularity of and interest in mobile games, there has been little research that evaluates gender differences in users’ actual preferences for mobile game content, and the factors that influence entertainment and mobile-learning habits. To fill this void, this study examines different gender users’ experience of mobile English learning game adoption in order to identify the areas of development in Taiwan, using Uses and Gratification Theory, Expectation Confirmation Theory and experiential value. The integration of these theories forms the basis of an extended research concept. Users’ responses to questions about cognitive perceptions, confirmation, gratifications and continuous use were collected and analyzed with various factors derived from the theories.

Keywords: expectation confirmation theory, experiential value, gender difference, mobile game, uses and gratification

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Authors: Hooman Torabifard

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In the last few years, with the progress of technology and computers and artificial intelligence entry into all kinds of scientific and industrial fields, the lifestyles of human life have changed and in general, the way of humans live on earth has many changes and development. Until now, some of the changes has occurred in the context of digital images and image processing and still continues. However, besides all the benefits, there have been disadvantages. One of these disadvantages is the multiplicity of images with high volume and data; the focus of this paper is on improving and developing a method for summarizing and enhancing the productivity of these images. The general method used for this purpose in this paper consists of a set of methods based on data obtained from image processing and using the PSO (Particle swarm optimization) algorithm. In the remainder of this paper, the method used is elaborated in detail.

Keywords: image summarization, particle swarm optimization, image threshold, image processing

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Authors: J. Cadby, K. Miyazawa

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Information and Communication Technology (ICT) has been widely adopted into the agricultural landscape with advancements of mobile connectivity and data accessibility. In developed nations, mobile-technology is well integrated into marketing transactions, and also plays a crucial role in making data-driven decisions on-farm. In developing nations, mobile banking and access to agricultural extension services allow for informed decision-making and smoother transactions. In addition, the availability of updated and readily available market and climate data provides a negotiation platform, reducing economic risks for farmers worldwide. The total usage of mobile technology has risen over the past 20 years, and almost three-quarters of the world’s population subscribes to mobile technology. This study reviewed mobile technology integration into agricultural systems in developing and developed nations. Data from secondary sources were collected and investigated. The objectives of the study include a review of the success of mobile banking transactions in developing nations, and a review of application and SMS based services for direct marketing in both developed and developing nations. Rural farmers in developing countries with access to diverse m-banking options experienced increased access to farm investment resources with the use of mobile banking technology. Rural farmers involved in perishable crop production were also more likely to benefit from mobile platform sales participation. ICT programs reached through mobile application and SMS increased access to agricultural extension materials and marketing tools for demographics that faced literacy-challenges and isolated markets. As mobile technology becomes more ubiquitous in the global agricultural system, training and market opportunities to facilitate mobile usage in developing agricultural systems are necessary. Digital skills training programs are necessary in order to improve equal global adoption of ICT in agriculture.

Keywords: market participation, mobile banking, mobile technology, rural farming

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Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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