Search results for: full reference image quality assessment (FR-IQA)

Authors: David G. Maxinez, Andrés Ferreyra Ramírez, Liliana Castillo Sánchez, Nancy Adán Mendoza, Carlos Aviles Cruz

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This research describes the use of fuzzy logic in detection, assessment, analysis and evaluation of children with behavioral disorders. It shows how to acquire and analyze ambiguous, vague and full of uncertainty data coming from the input variables to get an accurate assessment result for each of the typologies presented by children with behavior problems. Behavior disorders analyzed in this paper are: hyperactivity (H), attention deficit with hyperactivity (DAH), conduct disorder (TD) and attention deficit (AD).

Keywords: alteration, behavior, centroid, detection, disorders, economic, fuzzy logic, hyperactivity, impulsivity, social

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: Anjushi Verma, Tirthankar Gayen

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Although, reliability is an important attribute of quality, especially for mission critical systems, yet, there does not exist any versatile model even today for the reliability assessment of component-based software. The existing Black Box models are found to make various assumptions which may not always be realistic and may be quite contrary to the actual behaviour of software. They focus on observing the manner in which the system behaves without considering the structure of the system, the components composing the system, their interconnections, dependencies, usage frequencies, etc.As a result, the entropy (uncertainty) in assessment using these models is much high.Though, there are some models based on operation profile yet sometimes it becomes extremely difficult to obtain the exact operation profile concerned with a given operation. This paper discusses the drawbacks, deficiencies and limitations of Black Box approaches from the perspective of various authors and finally proposes a conceptual model for the reliability assessment of software.

Keywords: black box, faults, failure, software reliability

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Authors: Sabo Elizabeth

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Electronic learning is increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. This approach is important in human capital development. An investigation of open distance and e-learning facilities and information need by open and distance learning students was carried out in Jalingo, Nigeria. Structured questionnaires were administered to 70 registered ODL students of the NOUN. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Assessment of the effectiveness of ODL facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women. A large proportion of the respondents are married and there are more matured students in ODL compared to the youth. A high proportion of the ODL students obtained qualifications higher than the secondary school certificate. The proportion of computer literate ODL students was high, and large number of the students does not own a laptop computer. Inadequate e -books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities in the study areas. Inadequate computer facilities and power back up caused inconveniences and delay in administering and use of e learning facilities. To a high extent, open and distance learning students needed information on university time table and schedule of activities, availability and access to books (hard and e-books) and reference materials. The respondents emphasized that contact with course coordinators via internet will provide a better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

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Authors: Hassan Ibrahim, Moses Anayo Mbah

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The idempotent generators in a finite full transformation and the digraph of full transformation semi group have been an interesting area of research in group theory. In this work, it characterized some idempotent elements in full transformation semigroup T_n by counting the strongly connected and disconnected digraphs, and also the weakly and unilaterally connected digraphs. The order for those digraphs was further obtained in T_n.

Keywords: digraphs, indempotent, semigroup, transformation

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Authors: Ria M. Caramoan, Analiza P. Rollon, Karl N. Vergel

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The Simple Interactive Models for Better Air Quality (SIM-air) is an integrated approach model that allows the available information to support the integrated urban air quality management. This study utilized the vehicular air pollution information system module of SIM-air for the assessment of vehicular emissions in Commonwealth Avenue, Quezon City, Philippines. The main objective of the study is to assess and predict the contribution of different types of vehicles to the vehicular emissions in terms of PM₁₀, SOₓ, and NOₓ at different policy and technology scenarios. For the base year 2017, the results show vehicular emissions of 735.46 tons of PM₁₀, 108.90 tons of SOₓ, and 2,101.11 tons of NOₓ. Motorcycle is the major source of particulates contributing about 52% of the PM₁₀ emissions. Meanwhile, Public Utility Jeepneys contribute 27% of SOₓ emissions and private cars using gasoline contribute 39% of NOₓ emissions. Ambient air quality monitoring was also conducted in the study area for the standard parameters of PM₁₀, S0₂, and NO₂. Results show an average of 88.11 µg/Ncm, 47.41 µg/Ncm and 22.54 µg/Ncm for PM₁₀, N0₂, and SO₂, respectively, all were within the DENR National Ambient Air Quality Guideline Values. Future emissions of PM₁₀, NOₓ, and SOₓ are estimated at different scenarios. Results show that in the year 2030, PM₁₀ emissions will be increased by 186.2%. NOₓ emissions and SOₓ emissions will also be increased by 38.9% and 5.5%, without the implementation of the scenarios.

Keywords: ambient air quality, emissions inventory, mobile air pollution, vehicular emissions

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Authors: Rachna Jain, Sushila Madan, Bindu Garg

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Cloud computing is the key powerhouse in numerous organizations due to shifting of their data to the cloud environment. In recent years it has been observed that cloud-based-services are being used on large scale for content storage, distribution and processing. Various issues have been observed in cloud computing environment that need to be addressed. Security and privacy are found topmost concern area. In this paper, a novel security model is proposed to secure data by utilizing CDN services like image to icon conversion. CDN Service is a content delivery service which converts an image to icon, word to pdf & Latex to pdf etc. Presented model is used to convert an image into icon by keeping image secret. Here security of image is imparted so that image should be encrypted and decrypted by data owners only. It is also discussed in the paper that how server performs multiplication and selection on encrypted data without decryption. The data can be image file, word file, audio or video file. Moreover, the proposed model is capable enough to multiply images, encrypt them and send to a server application for conversion. Eventually, the prime objective is to encrypt an image and convert the encrypted image to image Icon by utilizing homomorphic encryption.

Keywords: cloud computing, user data security, homomorphic encryption, image multiplication, CDN service

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Authors: Jibon Sharma, Alakjyoti Patowary, Moirangthem Nara Singh

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In experimental research it is very much essential to obtain the quality control of the system used for the experiment. NaI (Tl) scintillation detector is the most commonly used in radiation and medical physics for measurement of the gamma ray activity of various samples. In addition, the scintillation detector has a lot of applications in the elemental analysis of various compounds, alloys using activation analysis. In each application for quantitative analysis, it is very much essential to know the detection efficiency and resolution for different gamma energies. In this work, the energy dependence of efficiency and resolution of NaI (Tl) detector using gamma-ray spectroscopy are investigated. Different photon energies of 356.01 keV,511keV,661.60keV,1170 keV,1274.53 keV and 1330 keV are obtained from four radioactive sources (133Ba,22Na,137Cs and 60 Co) used in these studies. Values of full energy peak efficiencies of these gamma energies are found to be respectively 58.46%,10.15%,14.39%,1.4%,3.27% and 1.31%. The values of percent resolution for above different gamma ray energies are found to be 11.27%,7.27%,6.38%,5.17%,4.86% and 4.74% respectively. It was found that the efficiency of the detector exponentially decreases with energy and the resolution of the detector is directly proportional to the energy of gamma-ray.

Keywords: naI (Tl) gamma-ray spectrometer, resolution, full energy peak efficiency, radioactive sources

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Authors: Ali Y Al-Attraqchi, P. Rajeev, M. Javad Hashemi, Riadh Al-Mahaidi

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This paper presents a probabilistic incremental dynamic analysis (IDA) of a full reinforced concrete building subjected to column loss scenario for the assessment of progressive collapse. The IDA is chosen to explicitly account for uncertainties in loads and system capacity. Fragility curves are developed to predict the probability of progressive collapse given the loss of one or more columns. At a broader scale, it will also provide critical information needed to support the development of a new generation of design codes that attempt to explicitly quantify structural robustness.

Keywords: fire, nonlinear incremental dynamic analysis, progressive collapse, structural engineering

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

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In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

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Authors: Hussaini Garba Mohammed

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Background/Significance: The lack of data gathering is affecting NGOs world-wide in general to have good data information about educational and health related issues among communities in any country and around the world. For example, HIV/AIDS smoking (Tuberculosis diseases) and COVID-19 virus carriers is becoming a serious public health problem, especially among old men and women. But there is no full details data survey assessment from communities, villages, and rural area in some countries to show the percentage of victims and patients, especial with this world COVID-19 virus among the people. These data are essential to inform programming targets, strategies, and priorities in getting good information about data gathering in any society.

Keywords: reliable information, data assessment, data mining, data communication

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Authors: Chan Kwong Tung

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Since Baddeley and Hitch’s seminal research in 1974 on working memory (WM), this topic has been of great interest to language educators. Although there are some variations in the definitions of WM, recent findings in WM have contributed vastly to our understanding of language learning, especially its effects on second language acquisition (SLA). For example, the phonological component of WM (PWM) and the executive component of WM (EWM) have been found to be positively correlated with language learning. This paper discusses two general, yet highly relevant WM findings that could directly affect the effectiveness of Chinese Language (CL) vocabulary teaching and learning, as well as the quality of its assessment. First, PWM is found to be critical for the long-term learning of phonological forms of new words. Second, EWM is heavily involved in interpreting the semantic characteristics of new words, which consequently affects the quality of learners’ reading comprehension. These two ideas are hardly discussed in the Chinese literature, both conceptual and empirical. While past vocabulary acquisition studies have mainly focused on the cognitive-processing approach, active processing, ‘elaborate processing’ (or lexical elaboration) and other effective learning tasks and strategies, it is high time to balance the spotlight to the WM (particularly PWM and EWM) to ensure an optimum control on the teaching and learning effectiveness of such approaches, as well as the validity of this language assessment. Given the unique phonological, orthographical and morphological properties of the CL, this discussion will shed some light on the vocabulary acquisition of this Sino-Tibetan language family member. Together, these two WM concepts could have crucial implications for the design, development, and planning of vocabularies and ultimately reading comprehension teaching and assessment in language education. Hopefully, this will raise an awareness and trigger a dialogue about the meaning of these findings for future language teaching, learning, and assessment.

Keywords: Chinese Language, working memory, vocabulary assessment, vocabulary teaching

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Authors: Ado Ismail Sabo

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Statement of the Problem: The global trend in tertiary education institutions today is changing and moving towards engagement, promotion and marketing. The reason is to upscale reputation and impact positioning. More prominently, existing rivalry today seeks to draw-in the best and brightest students. A university or college is no longer just an institution of higher learning, but one adapting additional business nomenclature. Therefore, huge financial resources are invested by educational institutions to polish their image and improve their global and national ranking. In Nigeria, which boasts of a vast population of over 180 million people, some of whose patronage can bolster its education sector; standard of education continues to decline. Today, some Nigerian tertiary education institutions are shadows of their pasts, in terms of academic excellence. Quality has been relinquished because of the unquenchable quest by government officials, some civil servants, school heads and educators to amass wealth. It is very difficult to gain student satisfaction and their loyalty. Some of the student’s loyalties factor towards public higher educational institutions might be confusing. It is difficult to understand the extent to which students are satisfy on many needs. Some students might feel satisfy with the academic lecturers only, whereas others may want everything, and others will never satisfy. Due to these problems, this research aims to uncover the crucial factors influencing student loyalty and to examine if students’ satisfaction might impact mediate the relationship between service quality, organisational image and students’ loyalty towards public higher education institutions in Kano State, Nigeria. The significance of the current study is underscored by the paucity of similar research in the subject area and public tertiary education in a developing country like Nigeria as shown in existing literature. Methodology: The current study was undertaken by quantitative research methodology. Sample of 600 valid responses were obtained within the study population comprising six selected public higher education institutions in Kano State, Nigeria. These include: North West University Kano, Bayero University Kano, School of Management Studies Kano, School of Technology Kano, Sa’adatu Rimi College Kano and Federal College of Education (FCE) Kano. Four main hypotheses were formulated and tested using structural equation modeling techniques with Analysis of Moment Structure (AMOS Version 22.0). Results: Analysis of the data provided support for the main issue of this study, and the following findings are established: “Student Satisfaction mediates the relationship between Service Quality and Student Loyalty”, “Student Satisfaction mediates the relationship between Organizational Image and Student Loyalty” respectively. The findings of this study contributed to the theoretical implication which proposed a structural model that examined the relationships among overall Organizational image, service quality, student satisfaction and student loyalty. Conclusion: In addition, the findings offered a better insight to the managerial (higher institution of learning service providers) by focusing on portraying the image of service quality with student satisfaction in improving the quality of student loyalty.

Keywords: student loyalty, service quality, student satisfaction, organizational image

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Authors: O. Vanijajiva, K. Oumaree, N. Ngampak

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This research aims to study the level of perception and participation of Phranakhon Rajabhat University staff and to study the relationship between the levels of perception and participation with the score of University evaluation of quality assurance in education. The respondents were composed of 479 staffs. The tool used in this research is perceived and participation questionnaire of quality assurance in education of Phranakhon Rajabhat University. The results found that the most staffs are female with undergraduate education. Most 2 respondents are revealing educational staffs without academic position. The fact of times to gain knowledge of quality assurance in education is 1-3 times. The perception of knowledge about quality assurance in education is moderate (3.74 ± 0.65) with most respondent are more focus on university activity than quality assurance in education activity. The participation of quality assurance in education activities involved in moderate (3.17 ± 0.88), with most respondents more involved in student affair than quality assurance in education motion. For assessment of the relationship of perception and participation of quality assurance in education are average score (4.31 ± 0.16) showed that the level of perception and participation was associated with university evaluation in very low level (r = -0.103 and -0.121, respectively), while perception and participation are correlated with the moderate level (r = 0.691).

Keywords: quality assurance education, awareness, participation, higher education, Thailand

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Authors: Md. Enamul Haque, Abdullah Al Kaisan, Mahmudur R. Saniat, Aminur Rahman

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In this paper, we have implemented both sequential and parallel version of fractal image compression algorithms using CUDA (Compute Unified Device Architecture) programming model for parallelizing the program in Graphics Processing Unit for medical images, as they are highly similar within the image itself. There is several improvements in the implementation of the algorithm as well. Fractal image compression is based on the self similarity of an image, meaning an image having similarity in majority of the regions. We take this opportunity to implement the compression algorithm and monitor the effect of it using both parallel and sequential implementation. Fractal compression has the property of high compression rate and the dimensionless scheme. Compression scheme for fractal image is of two kinds, one is encoding and another is decoding. Encoding is very much computational expensive. On the other hand decoding is less computational. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification an inseparable feature of the fractal compression would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression.

Keywords: accelerated GPU, CUDA, parallel computing, fractal image compression

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Authors: Mahdiar Hosseighadiry, Farnaz Fotovatikhah, Razali Ismail, Mohsen Khaledian, Mehdi Saeidemanesh

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In this paper, a new low-power high-performance full adder is presented based on a new design method. The proposed method relies on pass gate design and provides full-swing circuits with minimum number of transistors. The method has been applied on SUM, COUT and XOR-XNOR modules resulting on rail-to-rail intermediate and output signals with no feedback transistors. The presented full adder cell has been simulated in 45 and 32 nm CMOS technologies using HSPICE considering parasitic capacitance and compared to several well-known designs from literature. In addition, the proposed cell has been extensively evaluated with different output loads, supply voltages, temperatures, threshold voltages, and operating frequencies. Results show that it functions properly under all mentioned conditions and exhibits less PDP compared to other design styles.

Keywords: full adders, low-power, high-performance, VLSI design

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Authors: Ketwadee Madden

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Product or service image is among the vital factors that predict individuals’ choice of buying a product or services, goes to a place or attached to a person. Similarly, in the context of tourism, the destination image is a very important factor to which tourist considers before making their tour destination decisions. In light of this, the objective of this study is to conceptually investigate among French tourists, the determinants of Thailand’s tourism destination image. For this objective to be achieved, prior studies were reviewed, leading to the development of conceptual framework highlighting the determinants of destination image. In addition, this study develops some hypotheses that are to be empirically investigated. Aside these, based on the conceptual findings, suggestions on how to motivate European tourists to chose Thailand as their preferred tourism destination were made.

Keywords: cognitive destination image, affective destination image, motivations, risk perception, word of mouth

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Authors: Tahir Iqbal, Mumtaz Ali, Syed Wajahat Kareem, Muhammad Harris

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Digital information is expanding in exponential order in our life. Information that is residing online and offline are stored in huge repositories relating to every aspect of our lives. Getting the required information is a task of retrieval systems. Content based image retrieval (CBIR) is a retrieval system that retrieves the required information from repositories on the basis of the contents of the image. Time is a critical factor in retrieval system and using indexed views with CBIR system improves the time efficiency of retrieved results.

Keywords: content based image retrieval (CBIR), indexed view, color, image retrieval, cross correlation

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Authors: Nor Fazlina Iryani Abdul Hamid, Mohamad Khatim Hasan

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Evolution of software quality measurement has been started since McCall introduced his quality model in year 1977. Starting from there, several software quality models and software quality measurement methods had emerged but none of them focused on telecommunication industry. In this paper, the implementation of software quality measurement system for telecommunication industry was compulsory to accommodate the rapid growth of telecommunication industry. The quality value of the telecommunication related software could be calculated using this system by entering the required parameters. The system would calculate the quality value of the measured system based on predefined quality metrics and aggregated by referring to the quality model. It would classify the quality level of the software based on Net Satisfaction Index (NSI). Thus, software quality measurement system was important to both developers and users in order to produce high quality software product for telecommunication industry.

Keywords: software quality, quality measurement, quality model, quality metric, net satisfaction index

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Authors: Zainab Magaji Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

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The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: validation, verification, formal, theorem prover

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Authors: Youngseok Kim, Chul Park, Jonghwa Yi, Sangsik Choi

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The 2-MHz Side Scan SONAR (SSS) attached to the boat for inspection of underwater structures is affected by shaking. It is difficult to determine the exact scale of damage of structure. In this study, a motion sensor is attached to the inside of the 2-MHz SSS to get roll, pitch, and yaw direction data, and developed the image stabilization tool to correct the sonar image. We checked that reliable data can be obtained with an average error rate of 1.99% between the measured value and the actual distance through experiment. It is possible to get the accurate sonar data to inspect damage in underwater structure.

Keywords: image stabilization, motion sensor, safety inspection, sonar image, underwater structure

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: Lan Du, Yan Wang, Hui Dai

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Synthetic aperture radar (SAR) image change detection has recently become a challenging problem owing to the existence of speckle noises. In this paper, an unsupervised distribution-free change detection for SAR image based on scale-invariant feature transform (SIFT) keypoints and segmentation is proposed. Firstly, the noise-robust SIFT keypoints which reveal the blob-like structures in an image are extracted in the log-ratio image to reduce the detection range. Then, different from the traditional change detection which directly obtains the change-detection map from the difference image, segmentation is made around the extracted keypoints in the two original multitemporal SAR images to obtain accurate changed region. At last, the change-detection map is generated by comparing the two segmentations. Experimental results on the real SAR image dataset demonstrate the effectiveness of the proposed method.

Keywords: change detection, Synthetic Aperture Radar (SAR), Scale-Invariant Feature Transformation (SIFT), segmentation

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Authors: Hyoup-Sang Yoon

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The quality of video transmitted by mobile ad hoc networks (MANETs) can be influenced by several factors, including protocol layers; parameter settings of each protocol. In this paper, we are concerned with understanding the functional relationship between these influential factors and objective video quality in MANETs. We illustrate a systematic statistical design of experiments (DOE) strategy can be used to analyse MANET parameters and performance. Using a 2k factorial design, we quantify the main and interactive effects of 7 factors on a response metric (i.e., mean opinion score (MOS) calculated by PSNR with Evalvid package) we then develop a first-order linear regression model between the influential factors and the performance metric.

Keywords: evalvid, full factorial design, mobile ad hoc networks, ns-2

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

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Authors: James P. Takona

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Most of the global population has never lived through a pandemic, and thus there is so much that remains unknown about students' capacity for resiliency under such environments and circumstances and what a timeline for full recovery will look like. The session will guide participants to focus on misinformation and disinformation in the context of recent crisis events, with specific reference to how information flows across. Particular focus will be given to the flow of information in mediated technology and platforms with particular reference to K-12 and teacher preparation program environments. The paper will draw on theories and responses from the sociology of disaster, the social psychology of rumoring, and published studies on disinformation and misinformation. Applications will be identified and applied in the context of online information-sharing during crisis events. The session will offer the application of the Center for Contagious Diseases' Crisis and Emergency Risk Communication model to understand the themes and evolution of misinformation and disinformation. The paper will invite session participants to suggest and interact with raised challenges on the impact of dis-and misinformation.

Keywords: Sociology of disaster, misinformation, dis-information, Social Psychology of rumors

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Authors: Cristian Cazacu, Bela Kobulniczky

Abstract:

Even though nowadays the median area of the Bucharest’s Sector 1 owns one of the best reputations in terms of quality of life level, the problems in urban planning from the last twenty years, as well as those related to the urban environment, became more and more obvious and shrill. And all this happened as long as non-compliance with urban and spatial planning laws, corroborated with uncontrolled territorial expansion on certain areas and faulty management of public and private spaces were more acute. The action of all these factors has been felt more and more strongly in the territory in the last twenty years, generating the degradation of the quality of the urban environment and affecting in parallel the general level of the inhabitants¬’ quality of life. Our methodology is based on analyzing a wide range of environmental parameters and it is also based on using advanced resources and skills for mapping planning and environmental dysfunctions as well as the possibility of integrating information into GIS programs, all data sets corroborated with problems related to spatial planning management and inaccuracies of the urbanistic sector. In the end, we managed to obtain a calculated and realistic image of the dysfunctions and a quantitative view of their magnitude in the territory. We also succeeded to create a full general map of the degree of degradation of the urban environment by typologies of urban tissues. Moreover, the methods applied by us can also be used globally to calculate and create realistic images and intelligent maps over the quality of the environment in areas larger than this one. Our study shows that environmental degradation occurred differently in the urban tissues from our study area, depending on several factors, reviewing the faulty way in which the processes of recovery / urban regeneration of the gap in recent years have led to the creation of new territorial dysfunctions. The general, centralized results show that the analyzed space has a much wider range of problems than initially thought, although notoriety and social etiquette place them far above other spaces from the same city of study.

Keywords: environment, GIS, planning, urban tissues

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Authors: Marian Lissett Olaya

Abstract:

This article examined the factors associated with incorporating peer assessment into English language classes in a public university in Colombia. This is done in the context of writing English class for 4th-semester students. The research instruments consisted of peer assessment questionnaires, student diaries, and interviews. Findings showed that among the factors, motivation, frustration, anxiety, and lack of confidence appeared. Data revealed that peer assessment enables students to write competencies through training, teachers' guidance, and the provision of a collaborative environment.

Keywords: writing skills, peer assessment, formative assessment, language acquisition

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