Search results for: pervasive computing

Authors: Dawei Cai

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In this paper, we present an autonomous guidance service by combining the position information from NFC and the orientation information from a 6 axis acceleration and terrestrial magnetism sensor. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor. If visitors want to know some explanation about an exhibit in front of him, what he has to do is just lift up his mobile device. The identification program will automatically identify the status based on the information from NFC and MEMS, and start playing explanation content for him. This service may be convenient for old people or disables or children.

Keywords: NFC, ubiquitous computing, guide sysem, MEMS

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

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The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractively. Thus, this study intends to introduce the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN and LR to forecast the flavor of grapes juice in real data, the result shows that SVR is more suitable and effective at predicting performance.

Keywords: flavor forecasting, artificial neural networks, Support Vector Regression, China

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Authors: Lubna Azmi, Ila Shukla, Shyam Sundar Gupta, Padam Kant, Ch. V. Rao

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Gastric ulcer is a major global health threat, and it is the leading cause of stomach cancer death worldwide. Helicobacter pylori bacteriumis the most important etiologic factor for gastric ulcer. This infection is highly pervasive in South Asian developing countries, especially in India, Nepal, Srilanka etc. due to diversification in geographic area. Pathophysiology of gastric mucosal damage associated with non-invasive bacterium has not justified in detail, but it leads to change in histopathology, immunochemistry of the gastric and duodenal reason of host. The mechanism responsible for bacteria tissue tropism and mucosal damage in stomach variance during the disease is not clearly described and understood scientifically in treatment and control of pathogenic organisms. Polyphenols are secondary metabolites of plants and are generally involved in defense against aggression by pathogens. 2-(3,4-dihydroxyphenyl)-3,5,7-trihydroxychromen-4-one and 1-hydroxy-5,7-dimethoxy-2-naphthalene-carboxaldehyde are polyphenolic compound obtained from popular Indian medicinal plants ghavpatta (ArgeriaspeciosaLinn.f) andBael (Aeglemarmelos) have long been used in traditional Ayurvedic Indian medicine for various diseases. They have promising effects on ulcer, as detailed investigation has made in our laboratory. Therefore, the aim of present study is to explore membrane –dependent morphogenesis of H. pylori and associated apoptosis-mediated cell death. Based on this we analyzed immune gene expression in stomach of experimental animals with H. pylori, using quantitative reverse transcription polymerase chain reaction(q RT-PCR). This revealed rapid induction of prostaglandin, interferon I (INF-I), interferon II (INF-II) and INF-I associated genes in the infected animal. Ultrastructural changes associated with H. pylori will be taken for advanced studies. This investigation shows that the biomarkers eradicate H. pylori bacterium caused gastric ulcer which is a major risk factor for gastric cancer.

Keywords: gastric ulcer, Helicobacter pylori, immunochemistry, polyphenols

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Authors: C. P. Autry, A.W. Roscoe

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Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: authentication, enterprise IoT cybersecurity, PKI/TTP, IoT space

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Authors: Giovana Perini-Loureiro

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The purpose of this research was to identify whether the nominalizations terminating in -TION in the academic discourse of native English speakers contain the arguments required by their input verbs. In the perspective of functional linguistics, ideational metaphors, with nominalization as their most pervasive realization, are lexically dense, and therefore frequent in formal texts. Ideational metaphors allow the academic genre to instantiate objectification, de-personalization, and the ability to construct a chain of arguments. The valence of those nouns present in nominalizations tends to maintain the same elements of the valence from its original verbs, but these arguments are not always expressed. The initial hypothesis was that these arguments would also be present alongside the nominalizations, through anaphora or cataphora. In this study, a qualitative analysis of the occurrences of the five more frequent nominalized terminations in -TION in academic texts was accomplished, and thus a verification of the occurrences of the arguments required by the original verbs. The assembling of the concordance lines was done through COCA (Corpus of Contemporary American English). After identifying the five most frequent nominalizations (attention, action, participation, instruction, intervention), the concordance lines were selected at random to be analyzed, assuring the representativeness and reliability of the sample. It was possible to verify, in all the analyzed instances, the presence of arguments. In most instances, the arguments were not expressed, but recoverable, either in the context or in the shared knowledge among the interactants. It was concluded that the realizations of the arguments which were not expressed alongside the nominalizations are part of a continuum, starting from the immediate context with anaphora and cataphora; up to a knowledge shared outside the text, such as specific area knowledge. The study also has implications for the teaching of academic writing, especially with regards to the impact of nominalizations on the thematic and informational flow of the text. Grammatical metaphors are essential to academic writing, hence acknowledging the occurrence of its arguments is paramount to achieve linguistic awareness and the writing prestige required by the academy.

Keywords: corpus, functional linguistics, grammatical metaphors, nominalizations, academic English

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Authors: R. Pargas, M. Reba

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Since 2006, the School of Computing and the Department of Mathematical Sciences have collaborated on several industry and NSF grants to develop new uses of technology in teaching and learning. Clemson University’s Creative Inquiry Program allowed computer science and mathematics students to earn credit each semester for participating in seminars which introduced them to new areas for independent research. We will discuss how the development of three interactive instructional apps for Calculus resulted not only in a useful product, but also in unique educational benefits for both the computer science students and the mathematics students, graduate and undergraduate, involved in the development process.

Keywords: calculus, apps, programming, mathematics

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Authors: Jaber Nikpouri, Arsalan Amralizadeh

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In robotics manipulators, the trajectory should be optimum, thus the torque of the robot can be minimized in order to save power. This paper includes an optimal path planning scheme for a robotic manipulator. Recently, techniques based on metaheuristics of natural computing, mainly evolutionary algorithms (EA), have been successfully applied to a large number of robotic applications. In this paper, the improved BBO algorithm is used to minimize the objective function in the presence of different obstacles. The simulation represents that the proposed optimal path planning method has satisfactory performance.

Keywords: biogeography-based optimization, path planning, obstacle detection, robotic manipulator

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Authors: Janusz Bobulski, Kamila Pasternak

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Despite many years of effort and research, the problem of waste management is still current. So far, no fully effective waste management system has been developed. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.

Keywords: waste management, environmental protection, image processing, computer vision

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Authors: Diego Liberati

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Standard molecular modeling is traditionally done through Schroedinger equations via the help of powerful tools helping to manage them atom by atom, often needing High Performance Computing. Here, a full portfolio of new tools, conjugating statistical inference in the so called eXplainable Artificial Intelligence framework (in the form of Machine Learning of understandable rules) to the more traditional modeling and simulation control theory of mixed dynamic logic hybrid processes, is offered as quite a general purpose even if making an example to a popular chemical physics set of problems.

Keywords: understandable rules ML, k-means, PCA, PieceWise Affine Auto Regression with eXogenous input

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Authors: Zerrin Akter Anni

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The media's role in shaping perceptions of violence against women (VAW) and their portrayal in news reporting significantly influences our understanding of this critical issue. My research delves into the portrayal of violence against women in mainstream media, using the prominent case of Dr. Rumana Manzur, a former UBC Fulbright Scholar from Bangladesh who suffered a brutal assault by her ex-husband in June 2011. Employing a qualitative research approach, this study uses an ethnographic media analysis method to scrutinize news reports of the aforementioned case from selected newspapers in Bangladesh. The primary objectives are to investigate how the popular news media in Bangladesh addresses the issue of violence against women and frames the victims of such violence. The findings of this research highlight that news media can perpetuate gender stereotypes and subtly shift blame onto the victim through various techniques, creating intricate interactions between the reader and the text. These techniques include sensationalized headlines, textual content, and graphic images. This victim-blaming process not only retraumatizes the survivor but also distorts the actual facts when presenting the case to a larger audience. Consequently, the representation of violence against women cases in media, particularly the portrayal of women as victims during reporting, significantly impacts our collective comprehension of this issue. In conclusion, this paper asserts that the Bangladeshi media, particularly news outlets, in conjunction with society, continue to follow a pattern of depicting gender-based violence in ways that devalue the image of women. This research underscores the need for critical analysis of media representations of violence against women cases, as they can perpetuate harmful stereotypes and hinder efforts to combat this pervasive problem. Therefore, the outcome of this research is to comprehend the complex dynamics between media and violence against women, which is essential for fostering a more empathetic and informed society that actively works towards eradicating this problem from our society.

Keywords: media representation, violence against women (vaw), ethnographic media analysis, victim-blaming, sensationalized headline

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Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

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Authors: Gete Umbrey, Saifur Rahman

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Graphs are found to be most capable in computing, and its abstract structures have been applied in some specific computations and algorithms like in phase encoding controller, processor microcontroller, and synthesis of a CMOS switching network, etc. Being motivated by these works, we develop an independent approach to study semiring structures and various properties by defining the binary operations which in fact, seems analogous to an existing definition in some sense but with a different approach. This work emphasizes specifically on the construction of semigroup and semiring structures on the set of undirected graphs, and their properties are investigated therein. It is expected that the investigation done here may have some interesting applications in theoretical computer science, networking and decision making, and also on joining of two network systems.

Keywords: graphs, join and union of graphs, semiring, weighted graphs

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Authors: Jaya Mathew

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Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

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Authors: Muhammad Rezal Kamel Ariffin, Muhammad Asyraf Asbullah

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The square root modulo problem is a known primitive in designing an asymmetric cryptosystem. It was first attempted by Rabin. Decryption failure of the Rabin cryptosystem caused by the 4-to-1 decryption output is overcome efficiently in this work. The proposed scheme to overcome the decryption failure issue (known as the AAβ-cryptosystem) is constructed using a simple mathematical structure, it has low computational requirements and would enable communication devices with low computing power to deploy secure communication procedures efficiently.

Keywords: Rabin cryptosystem, 4-to-1 decryption failure, square root modulo problem, integer factorization problem

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Authors: Nazeema Ahmed

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This paper reports on the development of a student peer mentoring programme at a higher education institution. The programme is dependent on volunteering senior undergraduate students who are trained to mentor first-year students studying towards an engineering degree. The evaluation of the programme took the form of first-year students completing a self-report paper questionnaire at the onset of a lecture and mentors completing their questionnaire electronically. The evaluation yielded mixed findings. Peer mentoring clearly benefited some students in their adjustment to the institution. Specific mentors’ personal attributes enabled the establishment of successful mentoring relationships, where encouragement, advice and academic assistance was provided. Gains were reciprocal with mentors reporting that the programme contributed towards their personal development. Confidence in the programme was expressed in mentors feeling that it was an initiative worth continuing and first-year students agreeing that it be recommended to future first-year students. This was despite many unfavourable experiences of mentors where their professionalism and commitment to the programme was suspect. It is evident that while mentors began with noble intentions they appear either to lose interest or become overwhelmed with their own workload as the academic year progresses. On the other hand, some mentors reported feeling challenged by the apathy of first-year students who failed to maximise the opportunity available to them. The different attitudes towards mentoring that manifested as a mentoring culture in some departments were particularly pertinent to its successful implementation. The findings point to the key role of academic staff in the mentoring programme who model the mentoring relationship in their interaction with student mentors. While their involvement in the programme may be perceived as a drain on resources in an already demanding academic teaching environment, it is imperative that structural changes be put in place for the programme to be both efficient and sustainable. A pervasive finding concerns the evolving institutional culture of student development in the faculty. Mentors and first-year students alike alluded to the potential of the mentoring programme provided it is seriously endorsed at both the departmental and faculty level. The findings provide a foundation from which to develop the programme further and to begin improving its capacity for maximizing student retention in South African higher education.

Keywords: engineering students, first-year students, peer mentoring

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Wahhaj Ahmed Farooqi, Bilal Ahmad, Sandra Maritza Zambrano Bernal

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In view of structural engineering, monitoring of structural responses over time is of great importance with respect to recent developments of construction technologies. Recently, developments of advanced computing tools have enabled researcher’s better execution of structural health monitoring (SHM) and control systems. In the last decade, building information modeling (BIM) has substantially enhanced the workflow of planning and operating engineering structures. Typically, building information can be stored and exchanged via model files that are based on the Industry Foundation Classes (IFC) standard. In this study a modeling approach for semantic modeling of SHM and control systems is integrated into the BIM methodology using the IFC standard. For validation of the modeling approach, a laboratory test structure, a four-story shear frame structure, is modeled using a conventional BIM software tool. An IFC schema extension is applied to describe information related to monitoring and control of a prototype SHM and control system installed on the laboratory test structure. The SHM and control system is described by a semantic model applying Unified Modeling Language (UML). Subsequently, the semantic model is mapped into the IFC schema. The test structure is composed of four aluminum slabs and plate-to-column connections are fully fixed. In the center of the top story, semi-active tuned liquid column damper (TLCD) is installed. The TLCD is used to reduce effects of structural responses in context of dynamic vibration and displacement. The wireless prototype SHM and control system is composed of wireless sensor nodes. For testing the SHM and control system, acceleration response is automatically recorded by the sensor nodes equipped with accelerometers and analyzed using embedded computing. As a result, SHM and control systems can be described within open BIM, dynamic responses and information of damages can be stored, documented, and exchanged on the formal basis of the IFC standard.

Keywords: structural health monitoring, open building information modeling, industry foundation classes, unified modeling language, semi-active tuned liquid column damper, nondestructive testing

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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: Ahmad Khoirul Umam

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This paper investigates the role of vested interests and its impacts on anti-corruption agenda in Indonesia following the collapse of authoritarian regime in 1998. A pervasive and rampant corruption has been believed as the main cause of the state economy’s fragility. Hence, anti-corruption measures were implemented by applying democratization and market liberalization since the establishment of a consolidated democracy which go hand in hand with a liberal market economy is convinced to be an efficacious prescription for effective anti-corruption. The reform movement has also mandated the establishment of the independent, neutral and professional special anti-corruption agency namely Corruption Eradication Commission (KPK) to more intensify the fight against the systemic corruption. This paper will examine whether these anti-corruption measures have been effective to combat corruption, and investigate to what extend have the anti-corruption efforts, especially those conducted by KPK, been impeded by the emergence of a nexus of vested interests as the side-effect of democratization and market liberalization. Based on interviews with key stakeholders from KPK, other law enforcement agencies, government, prominent scholars, journalists and NGOs in Indonesia, it is found that since the overthrow of Soeharto, anti-corruption movement in the country have become more active and serious. After gradually winning the hearth of people, KPK successfully touched the untouchable corruption perpetrators who were previously protected by political immunity, legal protection and bureaucratic barriers. However, these changes have not necessarily reduced systemic and structural corruption practices. Ironically, intensive and devastating counterattacks were frequently posed by the alignment of business actors, elites of political parties, government, and also law enforcement agencies by hijacking state’s instruments to make KPK deflated, powerless, and surrender. This paper concludes that attempts of democratization, market liberalization and the establishment of anti-corruption agency may have helped Indonesia to reduce corruption. However, it is still difficult to imply that such anti-corruption measures have fostered the more effective anti-corruption works in the newly democratized and weakly regulated liberal economic system.

Keywords: vested interests, democratization, market liberalization, anti-corruption, Indonesia

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Authors: Ahmad Absetan, Mahdi Nooshyar

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The importance map is an image-based measure and is a core part of the resizing algorithm. Importance measures include image gradients, saliency and entropy, as well as high level cues such as face detectors, motion detectors and more. In this work we proposed a new method to calculate the importance map, the importance map is generated automatically using a novel combination of image edge density and Harel saliency measurement. Experiments of different type images demonstrate that our method effectively detects prominent areas can be used in image resizing applications to aware important areas while preserving image quality.

Keywords: content-aware image resizing, visual saliency, edge density, image warping

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Authors: Emanuel Guariglia

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In this paper we deal with Chebyshev wavelets. We analyze their properties computing their Fourier transform. Moreover, we discuss the differential properties of Chebyshev wavelets due the connection coefficients. The differential properties of Chebyshev wavelets, expressed by the connection coefficients (also called refinable integrals), are given by finite series in terms of the Kronecker delta. Moreover, we treat the p-order derivative of Chebyshev wavelets and compute its Fourier transform. Finally, we expand the mother wavelet in Taylor series with an application both in fractional calculus and fractal geometry.

Keywords: Chebyshev wavelets, Fourier transform, connection coefficients, Taylor series, local fractional derivative, Cantor set

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Authors: S. Bae, J. Shin, S. Lee

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As the development of smart devices such as Smart TV, Smartphone, Tablet PC, Laptop, the interest in N-Screen Services that can be cross-linked with heterogeneous devices is increasing. N-Screen means User-centric services that can share and constantly watch multimedia contents anytime and anywhere. However, the existing N-Screen system has the limitation that N-Screen system has to implement the application for each platform and device to provide multimedia service. To overcome this limitation, Multimedia N-Screen Service System is proposed through the web, and it is independent of different environments. The combination of Web and cloud computing technologies from this study results in increasing efficiency and reduction in costs.

Keywords: N-screen, web, cloud, multimedia

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Authors: Saeed Saffar-Heidari

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This article aims to study the recent Iranian national uprising of “Women, Life, Freedom” as a site of memory which renders the political possibility of imagining the post-Islamic futures in Iran. “Women, Life, Freedom” movement in Iran has been arguably the most pervasive social movement since the Islamic Revolution (1979) as it has posed serious issues and conflicts for the present Islamic state in Iran. The core argument of this article, however, is oriented toward the critical role of collective memory as a means of political transition and revolutionary mobilization. “Women, Life, Freedom” movement, among other things, has revitalized the popular binary opposition of pre-1979 and post-1979 Iran through which the Ancien Régime or the pre-1979 era is likely to be interpreted, read, and remembered in terms of present post-1979 cultural and political demands. As remembering involves everyday participation in shaping and reshaping the past through new codes, criteria, and values, it is argued that the presentist refashioning and remembering of the pre-1979 monarchical era has been one of the major facilitatory forces for the on-going revolutionary mobilization in Iran. The construction of the pre-1979 memory and the return of the dynastic specter has played a significant role in revolutionary mobilization as it has provided the protesters with the possible perspectives of post-Islamic regime in Iran. Additionally, the question of compulsory “Hijab” (veiling) as the prime mover of "Women, Life, Freedom” movement in Iran has strongly contributed to the everyday comparative discourse of pre/post 1979 memory. According to this presentist remembering of pre-1979, the Pahlavi dynasty would be conceived as a symbol of modernization, westernization, secularization, and non-compulsory Hijab. While the memory of the pre-revolutionary Iran is genuinely an imaginative as well as a constructed entity that finally culminates in the public condemnation of the very Islamic revolution (1979), it serves the enrichment of the Iranian political imagination as it paves the ways for the revolutionary mobilization and then the overthrowing of the Islamic regime in Iran. This article makes a case for the ways that the public narrative and discourse around the Islamic regime (especially the Islamic Hijab) led to the refashioning of the memory of pre-1979 era and inspired he revolutionary mobilization in Iran.

Keywords: post-islamic, utopias, memory, revolutionary, mobilization, Iran

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Authors: Vicario Marina, Ruiz Elena, Peredo Ruben, Bustos Eduardo

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the development group of Educational Computing of the National Polytechnic (IPN) in Mexico has been developing interactive resources at preschool level in an effort to improve learning in the Child Development Centers (CENDI). This work describes both a didactic architecture and a strategy for teaching English with digital stories using interactive resources available through a Web repository designed to be used in mobile platforms. It will be accessible initially to 500 children and worldwide by the end of 2015.

Keywords: instructional design, interactive resources, digital educational resources, story based English teaching, preschool education

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Mohammad Mosaddik Rahman

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This study embarks on an exploratory journey to assess the pervasive issue of heavy metal contamination in the water bodies along Chittagong Coast, Bangladesh. Situated along the mesmerizing Bay of Bengal, known for its potential as an emerging tourist haven, economic zone, ship breaking yard, confronts significant environmental hurdles. The core of these challenges lies in the contamination from heavy metals such as lead, cadmium, chromium, and mercury, which detrimentally impact both the ecological integrity and public health of the region. This contamination primarily stems from industrial activities, particularly those involving metallurgical and chemical processes, which release these metals into the environment, leading to their accumulation in soil and water bodies. The study's primary aim is to conduct a thorough assessment of heavy metal pollution levels, alongside an analysis of nutrient variations, focusing on nitrates and nitrites. Methodologically, the study leverages systematic sampling and advanced analytical tools like the Hach 3900 spectrophotometer to ensure precise and reliable data collection. The implications of heavy metal presence are multifaceted, affecting microbial and aquatic life, and posing severe health risks to the local population, including respiratory problems, neurological disorders, and an increased risk of cancer. The results of this study highlight the urgent need for effective mitigation strategies and regulatory measures to address this critical issue. By providing a comprehensive understanding of the environmental and public health implications of heavy metal contamination in Chittagong Coast, this research endeavours to serve as a catalyst for change, emphasising the need for pollution control and advancements in water management policies. It is envisioned that the outcomes of this study will guide stakeholders in collaborating to develop and implement sustainable solutions, ultimately safeguarding the region’s environment and public health.

Keywords: heavy metal, environmental health, pollution control policies, shipbreaking yard

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Authors: Rajendra Kumar Pandey

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Forest genetic resources not only represent regional biodiversity but also have immense value as the wealth for securing livelihood of poor people. These are vulnerable to ecological due to depletion/deforestation and /or impact of climate change. These resources of various plant categories are vulnerable on the floor of natural tropical forests, and leading to the threat on the growth and development of future forests. More than 170 species, including NTFPs, are in critical condition for their survival in natural tropical forests of Central India. Forest degradation, commensurate with biodiversity loss, is now pervasive, disproportionately affecting the rural poor who directly depend on forests for their subsistence. Looking ahead the interaction between forest and water, soil, precipitation, climate change, etc. and its impact on biodiversity of tropical forests, it is inevitable to develop co-operation policies and programmes to address new emerging realities. Forests ecosystem also known as the 'wealth of poor' providing goods and ecosystem services on a sustainable basis, are now recognized as a stepping stone to move poor people beyond subsistence. Poverty alleviation is the prime objective of the Millennium Development Goals (MDGs). However, environmental sustainability including other MDGs, is essential to ensure successful elimination of poverty and well being of human society. Loss and degradation of ecosystem are the most serious threats to achieving development goals worldwide. Millennium Ecosystem Assessment (MEA, 2005) was an attempt to identify provisioning and regulating cultural and supporting ecosystem services to provide livelihood security of human beings. Climate change may have a substantial impact on ecological structure and function of forests, provisioning, regulations and management of resources which can affect sustainable flow of ecosystem services. To overcome these limitations, policy guidelines with respect to planning and consistent research strategy need to be framed for conservation and sustainable development of forest genetic resources.

Keywords: climate change, forest ecosystem services, sustainable forest management, biodiversity conservation

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Authors: D. Zhang, H. Y. Du, G. W. Li, J. Zeng, D. W. Zuo, Y. P. You

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For the difficult issues of process selection, case-based reasoning technology is applied to computer aided process planning system for cold form tapping of internal threads on the basis of similarity in the process. A model is established based on the analysis of process planning. Case representation and similarity computing method are given. Confidence degree is used to evaluate the case. Rule-based reuse strategy is presented. The scheme is illustrated and verified by practical application. The case shows the design results with the proposed method are effective.

Keywords: case-based reasoning, internal thread, cold extrusion, process planning

Procedia PDF Downloads 511

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

Procedia PDF Downloads 214

Authors: Chahid K. Ghaddar

Abstract:

The spreadsheet engine is exploited via a non-conventional mechanism to enable novel worksheet solver functions for computational calculus. The solver functions bypass inherent restrictions on built-in math and user defined functions by taking variable formulas as a new type of argument while retaining purity and recursion properties. The enabling mechanism permits integration of numerical algorithms into worksheet functions for solving virtually any computational problem that can be modelled by formulas and variables. Several examples are presented for computing integrals, derivatives, and systems of deferential-algebraic equations. Incorporation of the worksheet solver functions with the ubiquitous spreadsheet extend the utility of the latter as a powerful tool for computational mathematics.

Keywords: calculus, differential algebraic equations, solvers, spreadsheet

Procedia PDF Downloads 364