Search results for: visual sensor networks

Authors: Sugandhi, Parteek Kumar, Sanmeet Kaur

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Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.

Keywords: avatar, dictionary, HamNoSys, hearing impaired, Indian sign language (ISL), sign language

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Authors: Yung-Hui Tang, Yan-Chiou Ku, Li-Chi Huang

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Aim: The aim of this study is to explore the effect of the Humanoid Diagram Teaching (HDT) strategy on novice nurses’ care ability and retention rate. Methods: This study was a quasi-experimental study using two groups concurrently with repeat measurements sample consisted of 24 novice nurses (12 in each experimental and control group) in a medical center in southern Taiwan. Both groups all received regular training program (nursing standard techniques and practices, concept map, mini-CEX, CbD, and clinical education and training), and experimental group added the HDT program. The HDT strategy includes the contents of patients’ body humanoid drawing and discussion for 30 minutes each time, three times a week, and continually for four weeks. The effectiveness of ＨDT was evaluated by mini-CEX, CbD and clinical assessment and retention rate at the 3rd month and 6th month. Results: The novice nurses' care ability were examined, only CbD score in the control group was improved in the 3rd month and with statistical difference, p = .003. The mini-CEX and CbD in the experimental group were significantly improved in both the first and third month with statistical differences p = .00. Although mini-CEX and CbD in the experimental group were higher than the control group, but there was no significant difference p > .05. Retention rate of the experimental group in the third month and sixth month was significantly higher than the control group, and there was a statistically significant difference p < .05. Conclusions: The study reveals that HDT strategy can help novice nurses learning, enhancing their knowledge and technical capability, analytical skills in case-based caring, and retention. The HDT strategy can be served as an effective strategy for novice training for better nurse retention rate.

Keywords: humanoid diagram teaching strategy, novice nurses retention, teaching strategy of nurse retention, visual learning mode

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Authors: K. Geetha Ramesh, A. Ramachandraiah

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In an internal building space, daylight becomes a powerful source of illumination. The challenge therefore, is to develop means of utilizing both direct and diffuse natural light in buildings while maintaining and improving occupant's visual comfort, particularly at greater distances from the windows throwing daylight. The geometrical features of windows in a building have significant effect in providing daylight. The main goal of this research is to develop an innovative window geometry, which will effectively provide the daylight component adequately together with internal reflected component(IRC) and also the external reflected component(ERC), if any. This involves exploration of a light redirecting system using fractal geometry for windows, in order to penetrate and distribute daylight more uniformly to greater depths, minimizing heat gain and glare, and also to reduce building energy use substantially. Of late the creation of fractal geometrical window and the occurrence of daylight illuminance due to such windows is becoming an interesting study. The amount of daylight can change significantly based on the window geometry and sky conditions. This leads to the (i) exploration of various fractal patterns suitable for window designs, and (ii) quantification of the effect of chosen fractal window based on the relationship between the fractal pattern, size, orientation and glazing properties for optimizing daylighting. There are a lot of natural lighting applications able to predict the behaviour of a light in a room through a traditional opening - a regular window. The conventional prediction methodology involves the evaluation of the daylight factor, the internal reflected component and the external reflected component. Having evaluated the daylight illuminance level for a conventional window, the technical performance of a fractal window for an optimal daylighting is to be studied and compared with that of a regular window. The methodologies involved are highlighted in this paper.

Keywords: daylighting, fractal geometry, fractal window, optimization

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Authors: Ahmed R. Z. Baghdadi, Ibrahim M. I. Hamoda,  Mona H. Gamal Eldein, Ibrahim Magdy Elnaggar

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Background: High-velocity low amplitude thrust (HVLAT) manipulation and low-velocity low amplitude (LVLA) mobilization are an effective treatment for low back pain (LBP). Purpose: This study compared the effects of HVLAT versus LVLA on pain, functional deficits and segmental mobility in treatment of chronic mechanical LBP. Methods: Ninety patients suffering from chronic mechanical LBP are classified to three groups; Thirty patients treated by HVLAT (group I), thirty patients treated by LVLA (group II) and thirty patients as control group (group III) participated in the study. The mean age was 28.00±2.92, 27.83±2.28 and 28.07±3.05 years and BMI 27.98±2.60, 28.80±2.40 and 28.70±2.53 kg/m2 for group I, II and III respectively. The Visual Analogue Scale (VAS), the Oswestry low back pain disability questionnaire and modified schoper test were used for assessment. Assessments were conducted two weeks before and after treatment with the control group being assessed at the same time intervals. The treatment program group one was two weeks single session per week, and for group II two sessions per week for two weeks. Results: The One-way ANOVA revealed that group I had significantly lower pain scores and Oswestry score compared with group II two weeks after treatment. Moreover, the mobility in modified schoper increased significantly and the pain scores and Oswestry scores decreased significantly after treatment in group I and II compared with control group. Interpretation/Conclusion: HVLAT is preferable to LVLA mobilization, possibly due to a beneficial neurophysiological effect by Stimulating mechanically sensitive neurons in the lumbar facet joint capsule.

Keywords: low back pain, manipulation, mobilization, low velocity

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Deepali Rastogi

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Natural dyes are considered to be eco-friendly as they cause no pollution and are safe to use. With the growing interest in natural dyes, new sources of natural dyes are being explored. Coconut (Cocos nucifera) is native to tropical eastern region. It is abundantly available in Asia, Africa and South America. While coconut has tremendous commercial value in food, oil, pharmaceutical and cosmetic industry, the most important use of coconut husk has been as coir which is used for making mats, ropes, etc. In the present study an attempt has been made to extract dye from the coconut husk and study its application on wool and silk. Dye was extracted from coconut husk in an aqueous medium at three different pH. The coconut husk fibres were boiled in water at different pH of 4, 7 and 9 for one hour. On visual inspection of the extracted dye solution, maximum colour was found to be extracted at pH 9. The solution was obtained in neutral medium whereas, no dye was extracted in acidic medium. Therefore, alkaline medium at pH 9 was selected for the extraction of dye from coconut husk. The extracted dye was applied on wool and silk at three different pH, viz., 4, 7 and 9. The effect of pre- and post- mordanting with alum and ferrous sulphate on the colour value of coconut husk dye was also studied. The L*a*b*/L*c*h* values were measured to see the effect of the mordants on the colour values of all the dyed and mordanted samples. Bright golden brown to dark brown colours were obtained at pH 4 on both wool and silk. The colour yield was not very good at pH 7 and 9. Mordanting with alum resulted in darker and brighter shades of brown, whereas mordanting with ferrous sulphate resulted in darker and duller shades. All the samples were tested for colourfastness to light, rubbing, washing and perspiration. Both wool and silk dyed with dye extracted from coconut husk exhibited good to excellent wash, rub and perspiration fastness. Fastness to light was moderate to good.

Keywords: coconut husk, wool, silk, natural dye, mordants

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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Authors: Normah Sulaiman, Yong Zhi Kang, Nor Hayati Hussain, Abdul Rehman Khalid

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Segara Ninda owned by Din Ku Meh, the governor of the province Satul, a Malay man with a big role liaising with Thailand. This mansion is part of the legacy he left behind among other properties in George Town, Penang, besides his family. The island’s geographical location is strategic which has benefitted it through important trade routes for Europe, Middle, East, India, and China in the past. Due to this reasoning, various architectural styles were introduced in Penang; Late Straits Eclectic style is one of the forms of the Colonial Architectural style widely spread as vernacular shophouses in George Town. Segara Ninda is located among the mixture of nouveau-riche, historical and heritage sites at the most important street; Penang Road, which dated back to the late 18th century. This paper examines the strait eclectic style that Segara Ninda encompasses. Acknowledging the mixture of colonial architecture in Georgetown, we argue that the mansion faces challenging issues in conservation processes to be vindicated. This is reflected by analysing the spatial layout, visual elements quality, and its activity through interviews with the occupants of the mansion. The focus will be on the understanding of building form, features, and functions; respecting the architectural spaces and their activity. The methodology applied is to promote our understanding of the mix of culture that the mansion holds through documentation, observation and measuring exercises. This offers a positional interpretation of the mix of culture that the mansion holds. This conservation effort will further contribute exposure to the public and recognize it in the society as its essence is a deficiency character to the existing built environment.

Keywords: eclectic, heritage, spatial organization, culture

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: Kruti Dave

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Social media marketing is an essential component of 21st-century business. Social media platforms enable small and medium-sized businesses to enhance brand recognition, generate leads and sales. However, the research on social media marketing is still fragmented and focuses on specific topics, such as effective communication techniques. Since the various ways in which social media impacts individuals and companies alike, the authors of this article focus on the origin, impacts, and current state of Social Media, emphasizing their significance as customer empowerment agents. It illustrates their potential and current responsibilities as part of the corporate business strategy and also suggests several methods to engage them as marketing tools. The focus of social media marketing ranges from defenders to explorers, the culture of Social media marketing encompasses the poles of conservatism and modernity, social media marketing frameworks lie between hierarchies and networks, and its management goes from autocracy to anarchy. This research proposes an integrative framework for small and medium-sized businesses through social media, and the influence of the same will be measured. This strategy will help industry experts to understand this new era. We propose an axiom: Social Media is always a function of marketing as a revenue generator.

Keywords: social media, marketing strategy, media marketing, brand awareness, customer engagement, revenue generator, brand recognition

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Authors: H. E. Amb. Terry Earthwind Nichols

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Over the years Ambassador Nichols observed that successful companies all have one thing in common - belief in people. His observations of people in many companies, industries, and countries have also concluded one thing - groups of achievers far exceed the expectations and timelines of their superiors. His experience with achieving this has brought forth a model for the 21st century that will not only exceed expectations of companies, but it will also set visions for the future of business globally. It is time for real discussion around the future of work and the business model that will set the example for the world. Methodologies: In-person observations over 40 years – Ambassador Nichols present during the observations. Audio-visual observations – TV, Cinema, social media (YouTube, etc.), various news outlet Reading the autobiography of some of successful leaders over the last 75 years that lead their companies from a distinct perspective your people are your commodity. Major findings: People who believe in the leader’s vision for the company so much so that they remain excited about the future of the company and want to do anything in their power to ethically achieve that vision. People who are achieving regularly in groups, division, companies, etcetera: Live more healthfully lowering both sick time off and on-the-job accidents. Cannot wait to physically get to work as much as they can to feed off the high energy present in these companies. They are fully respected and supported resulting in near zero attrition. Simply put – they do not “Burn Out”. Conclusion: To the author’s best knowledge, 20th century practices in business are no longer valid and people are not going to work in those environments any longer. The average worker in the post-covid world is better educated than 50 years ago and most importantly, they have real-time information about any subject and can stream injustices as they happen. The Consortium Model is just the model for the evolution of both humankind and business in the 21st century.

Keywords: business model, future of work, people, paradigm shift, business management

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Authors: R. Periyasamy, Deepak Joshi, Sneh Anand

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Foot posture assessment is important to evaluate foot type, causing gait and postural defects in all age groups. Although different methods are used for classification of foot arch type in clinical/research examination, there is no clear approach for selecting the most appropriate measurement system. Therefore, the aim of this study was to develop a system for evaluation of foot type as clinical decision-making aids for diagnosis of flat and normal arch based on the Arch Index (AI) and foot pressure distribution parameter - Power Ratio (PR) data. The accuracy of the system was evaluated for 27 subjects with age ranging from 24 to 65 years. Foot area measurements (hind foot, mid foot, and forefoot) were acquired simultaneously from foot pressure intensity image using portable PedoPowerGraph system and analysis of the image in frequency domain to obtain foot pressure distribution parameter - PR data. From our results, we obtain 100% classification accuracy of normal and flat foot by using the linear discriminant analysis method. We observe there is no misclassification of foot types because of incorporating foot pressure distribution data instead of only arch index (AI). We found that the mid-foot pressure distribution ratio data and arch index (AI) value are well correlated to foot arch type based on visual analysis. Therefore, this paper suggests that the proposed system is accurate and easy to determine foot arch type from arch index (AI), as well as incorporating mid-foot pressure distribution ratio data instead of physical area of contact. Hence, such computational tool based system can help the clinicians for assessment of foot structure and cross-check their diagnosis of flat foot from mid-foot pressure distribution.

Keywords: arch index, computational tool, static foot pressure intensity image, foot pressure distribution, linear discriminant analysis

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Authors: Taras Agryzkov, Jose L. Oliver, Leandro Tortosa, Jose Vicent

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This paper aims to demonstrate how network models can be used to understand and to deal with some aspects of urban complexity. As it is well known, the Theory of Architecture and Urbanism has been using for decades’ intellectual tools based on the ‘sciences of complexity’ as a strategy to propose theoretical approaches about cities and about architecture. In this sense, it is possible to find a vast literature in which for instance network theory is used as an instrument to understand very diverse questions about cities: from their commercial activity to their heritage condition. The contribution of this research consists in adding one step of complexity to this process: instead of working with one single primal graph as it is usually done, we will show how new network models arise from the consideration of two different primal graphs interacting in two layers. When we model an urban network through a mathematical structure like a graph, the city is usually represented by a set of nodes and edges that reproduce its topology, with the data generated or extracted from the city embedded in it. All this information is normally displayed in a single layer. Here, we propose to separate the information in two layers so that we can evaluate the interaction between them. Besides, both layers may be composed of structures that do not have to coincide: from this bi-layer system, groups of interactions emerge, suggesting reflections and in consequence, possible actions.

Keywords: graphs, mathematics, networks, urban studies

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Dedie Tooy, Rio Kolibu, Rio Putra, Herry Frits Pinatik, Daniel P. M. Ludong

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This study presents the design and development of a smart greenhouse prototype tailored to optimize Pak choi (Brassica chinensis L.) cultivation in tropical rural climates. Pak choi, a high-demand leafy vegetable in Indonesia, often experiences suboptimal growth due to elevated temperatures and humidity. The objective of this research is to design and develop an intelligent greenhouse to optimize pak choi cultivation in tropical rural climates. The design of a smart greenhouse provides a controlled environment to stabilize these conditions, but managing fluctuating temperature, humidity, and light in tropical regions remains challenging. This system regulates critical environmental factors, including temperature, humidity, irrigation system, and light, creating optimal conditions for Pak Choi. The prototype's effectiveness was evaluated by monitoring growth indicators such as leaf weight, freshness, and moisture content, alongside the consistency of the internal climate compared to external conditions. Results indicate that the smart greenhouse supports superior crop growth, enhances yield quality, and reduces environmental resource consumption. The irrigation control system test was carried out for 40 days. Researchers observed the results of the automatic system working according to the sensor value readings. The results of the temperature control system test work: when the air temperature in the greenhouse is more than 33 degrees, the condensation pump will turn on, and when the temperature is below 32 degrees, the pump will automatically turn itself off. The cycle repeats continuously. The results achieved pak coy can live up to 40 days. As part of our ongoing research, we are actively considering integrating double-layered roofs to improve insulation and reduce external temperature fluctuations, which could further enhance the effectiveness of the smart greenhouse.

Keywords: smart greenhouse, horticulture, rural tropical climate, sustainable agriculture

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Authors: Yanto Santosa, Yohanna Dalimunthe, Intan Purnamasari

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Expansion of Indonesia oil palm plantations has contributed significantly to the national revenue annually and has been able to absorb millions of workers. Behind all these positive contributions, such expansion was accused as the cause of the decline in wildlife populations such as mammal and herpetofauna. Research was carried out in 8 oil palm plantations in Riau Province of Indonesia from March to April 2016, to determine the impacts of oil palm plantations on mammal and herpetofauna biodiversity. Direct observation was conducted simultaneously equipped with camera traps placed (for mammal) on various land cover types. For mammals' survey, line transect method was used, and for herpetofauna, Visual Encounter Survey (VES) method was used. Landsat imagery was used to interpret land cover types 3 years prior to the establishment of the oil palm plantations. The study revealed that one year before the oil palm plantations was established, most the land covers were comprised of 49.96% rubber plantations, 35.99% secondary forest, 10.17% bare land, 3.03% shrubs and 0.84% mixed dryland farming-shrubs. Based on the number of species found, it was identified that on the average, mammal diversity in 4 of 8 oil palm plantations, showed a decrease by 14.29%-100%, whereas 2 plantations did not experienced any changes in the number of species and one plantation showed an increased in the number of mammal species. The plantations that experienced a reduction in the number of mammal’s diversity were previously dominated covered by secondary forest (40%) and rubber plantation (40%), while those experiencing no changes in the number of species were also dominated by secondary forest. The area with an increased number of mammal species was historically dominated by rubber plantation. On the contrary, significant results were shown for herpetofauna, where all study sites showed a sharp increase in the number of herpetofauna species, by 100%-225.00%.

Keywords: herpetofauna, impact, mammal, oil palm plantations

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Authors: C. C. Liang

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MSN used to be the most popular application for communicating among social networks, but Facebook chat is now the most popular. Facebook and MSN have similar characteristics, including usefulness, ease-of-use, and a similar function, which is the exchanging of information with friends. Facebook outperforms MSN in both of these areas. However, the adoption of Facebook and abandonment of MSN have occurred for other reasons. Functions can be improved, but users’ willingness to use does not just depend on functionality. Flow status has been established to be crucial to users’ adoption of cyber applications and to affects users’ adoption of software applications. If users experience flow in using software application, they will enjoy using it frequently, and even change their preferred application from an old to this new one. However, no investigation has examined choice behavior related to switching from Facebook to MSN based on a consideration of flow experiences and functions. This investigation discusses the flow experiences and functions of social-networking applications. Flow experience is found to affect perceived ease of use and perceived usefulness; perceived ease of use influences information ex-change with friends, and perceived usefulness; information exchange influences perceived usefulness, but information exchange has no effect on flow experience.

Keywords: consumer behavior, social media, technology acceptance model, flow experience

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Authors: Taleb L., Benarbia M., Boutira F. M., Allam H., Boukerche A.

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Introduction and purpose of the study: Meningiomas are the most common non-glial intracranial tumors in adults, accounting for approximately 30% of all central nervous system tumors. The aim of our study is to determine the epidemiological, clinical, therapeutic, and evolutionary characteristics of a cohort of patients with intracranial meningioma treated with radiotherapy at the Emir Abdelkader Cancer Center in Oran. Material and methods: This is a retrospective study of 44 patients during the period from 2014 to 2020. The overall survival and relapse-free survival curves were calculated using the Kaplan-Meier method. Results and statistical analysis: The median age of the patients was 49 years [21-76 years] with a clear female predominance (sex ratio=2.4). The average diagnostic delay was seven months [2 to 24 months], the circumstances of the discovery of which were dominated by headaches in 54.5% of cases (n=24), visual disturbances in 40.9% (n=18), and motor disorders in 15.9% (n=7). The seat of the tumor was essentially at the level of the base of the skull in 52.3% of patients (n=23), including 29.5% (n=13) at the level of the cavernous sinus, 27.3% (n=12) at the parasagittal level and 20.5% (n=9) at the convexity. The diagnosis was confirmed surgically in 36 patients (81.8%) whose anatomopathological study returned in favor of grades I, II, and III in respectively 40.9%, 29.5%, and 11.4% of the cases. Radiotherapy was indicated postoperatively in 45.5% of patients (n=20), exclusive in 27.3% (n=12) and after tumor recurrence in 27.3% of cases (n=18). The irradiation doses delivered were as follows: 50 Gy (20.5%), 54 Gy (65.9%), and 60 Gy (13.6%). With a median follow-up of 69 months, the probabilities of relapse-free survival and overall survival at three years are 93.2% and 95.4%, respectively, whereas they are 71.2% and 80.7% at five years. Conclusion: Meningiomas are common primary brain tumors. Most often benign but can also progress aggressively. Their treatment is essentially surgical, but radiotherapy retains its place in specific situations, allowing good tumor control and overall survival.

Keywords: diagnosis, meningioma, surgery, radiotherapy, survival

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Ghada M. R. Koura, Mohamed N. Mohamed, Ahmed M. F. El Shiwi

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Chronic mechanical Low back dysfunction (CMLBD) is the most common problem of the working-age population in modern industrial sociaty; it causes a substantial economic burden due to the wide use of medical services and absence from work. Aim of work: the aim of this study was to investigate the effect of positional release technique on patients with chronic mechanical low back pain. Materials and Methods: Thirty two patients from both sexes were diagnosed with CMLBP, aged 20 to 45 years and were divided randomly into two equal groups; sixteen patients each; group A (control group) received therapeutic exercises that include (Stretch and Strength exercises for back and abdominal muscles). Group B (experimental group) received therapeutic exercises with positional release technique; treatment was applied 3 days/week for 4 weeks. Pain was measured by Visual Analogue Scale, Lumbar range of motion was measured by Inclinometer and Functional disability was measured by Oswestry disability scale. Measurements were taken at two intervals pre-treatment and post-treatment. Results: Data obtained was analyzed via paired and unpaired t-Test. There were statistical differences between the 2 groups, where the experimental group showed greater improvement than control group. Conclusion: Positional release technique is considered as an effective treatment for reducing pain, functional disability and increasing lumbar range of motion in individuals with chronic mechanical low back pain.

Keywords: chronic mechanical low back pain, traditional physical therapy program, positional release technique, randomized controlled trial

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

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Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

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Authors: Zhao Yu, Zhi-Nan Zhang

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More and more interactive devices are used in the transportation service system. Our mobile phones, on-board computers, and Head-Up Displays (HUDs) can all be used as the tools of the in-car service system. People can access smart systems with different terminals such as mobile phones, computers, pads and even their cars and watches. Different forms of terminals bring the different quality of interaction by the various human-computer Interaction modes. The new interactive devices require good ergonomics design at each stage of the whole design process. According to the theory of human factors and ergonomics, this paper compared three types of interactive devices by four driving tasks. Forty-eight drivers were chosen to experience these three interactive devices (mobile phones, on-board computers, and HUDs) by a simulate driving process. The subjects evaluated ergonomics performance and subjective workload after the process. And subjects were encouraged to support suggestions for improving the interactive device. The result shows that different interactive devices have different advantages in driving tasks, especially in non-driving tasks such as information and entertainment fields. Compared with mobile phones and onboard groups, the HUD groups had shorter response times in most tasks. The tasks of slow-up and the emergency braking are less accurate than the performance of a control group, which may because the haptic feedback of these two tasks is harder to distinguish than the visual information. Simulated driving is also helpful in improving the design of in-vehicle interactive devices. The paper summarizes the ergonomics characteristics of three in-vehicle interactive devices. And the research provides a reference for the future design of in-vehicle interactive devices through an ergonomic approach to ensure a good interaction relationship between the driver and the in-vehicle service system.

Keywords: human factors, industrial ergonomics, transportation system, usability, vehicle user interface

Procedia PDF Downloads 139

Authors: Burcu Babadağ Savaş, Nihal Orlu, Güler Balcı Alparslan, Ertuğrul Çolak, Cengiz Korkmaz

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Introduction/objectives: We aimed to investigate the effect of humor on pain and state anxiety in patients with rheumatoid arthritis (RA) receiving biologic intravenous (IV) infusion therapy. Method: The study sample consisted of 36 patients who met the classification criteria for RA and inclusion criteria in a rheumatology outpatient clinic at a university hospital between September 2020 and November 2021. Two sample groups were formed: the intervention group (watching a comedy movie) (n=18) and the control group (n=18). The intervention group consisted of the patient watching a comedy movie of his/her choice from an archive created by the researchers during the biological IV infusion therapy (approximately 90-120 minutes). The data collection instruments used before and after the test were the descriptive identification form, the visual analog scale (VAS), and the state anxiety scale. Results: The mean VAS scores of patients in the intervention group were 5.05 ± 2.01 in the pre-test and 2.61 ± 1.91 in the post-test. The mean state anxiety scores of patients in the intervention group were 45.94 ± 9.97 in the pre-test and 34.22 ± 6.57 in the post-test. Thus, patients who watched comedy movies during biologic IV infusion therapy in the infusion center had a greater reduction in pain scores than the control group and the effect size was small. Although there was a decrease in state anxiety scores in both groups, there was no significant difference between groups and the effect size was not relevant. Conclusions: During IV infusion therapy, watching comedy movies is recommended as a nursing care intervention for reducing pain in patients with RA in cooperation with other health professionals.

Keywords: watching comedy movie, humor, pain, anxiety, nursing, care

Procedia PDF Downloads 139

Authors: Maryam Nazari, Atefeh Ghanbari, Saghar Noorinia

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Obesity, as an abnormal or excessive accumulation of fat, is caused by genetic, behavioral and environmental factors. Recently, obesity surgeries, such as bariatric surgery, as the last measure to control obesity, have attracted experts and society, especially women, attention, so knowing the possible complications of this major surgery and their control in reproductive age is of particular importance due to its effects on pregnancy outcomes. Bariatric surgery reduces the risk of diabetes and high blood pressure associated with pregnancy, premature birth, macrosomia, stillbirth and dumping syndrome. Although in the first months after surgery, nausea and vomiting caused by changes in intra-abdominal pressure are associated with an increased risk of malabsorption of micronutrients such as folic acid, iron, vitamin B1, D, calcium, selenium and phosphorus and finally, fetal growth disorder. Moreover, serum levels of micronutrients such as vitamin D, calcium, and iron in mothers who used to have bariatric surgery and their babies have been shown to be lower than in mothers without a history of bariatric surgery. Moreover, vitamin A deficiency is shown to be more widespread in pregnancies after bariatric surgery, which leads to visual problems in newborns and premature delivery. However, complications such as the duration of hospitalization of newborns in the NICU, disease rate in the first 28 days of life and congenital anomalies are not significantly different in babies born to mothers undergoing bariatric surgery compared to the control group. In spite of the vast advantages following obesity surgeries, due to the catabolic conditions and severe weight loss followed by such major intervention and the probability of nutrients malnutrition in a pregnant woman and her baby, after having surgery, at least 12 to 18 months should be considered to get pregnant as a recovery period. In addition, taking essential supplements before and at least 6 months after this approach is recommended.

Keywords: bariatric surgery, pregnancy, malnutrition, vitamin and mineral deficiency

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Authors: Harshan Baskar, Anirudh S. Chakravarthy, Prateek Garg, Divyam Goel, Abhijith S. Raj, Kshitij Kumar, Lakshya, Ravichandra Parvatham, V. Sushant, Bijay Kumar Rout

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In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a new benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve SSIM of 0.8962 and PSNR of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task, particularly for autonomous navigation applications, and we hope that our work will open up new frontiers in research. Our dataset and code will be made publicly available upon acceptance of our paper.

Keywords: dehazing, image enhancement, nighttime, computer vision

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Authors: Shima Nikanjam, Badiossadat Hassanpour, Adi Irfan Che Ani

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The design process in architecture education is based upon the Learning-by-Doing method, which leads students to understand how to design by practicing rather than studying. First-year design studios, as starting educational stage, provide integrated knowledge and skills of design for newly jointed architecture students. Within the basic design studio environment, students are guided to transfer their abstract thoughts into visual concrete decisions under the supervision of design educators for the first time. Therefore, introductory design studios have predominant impacts on students’ operational thinking and designing. Architectural design thinking is quite different from students’ educational backgrounds and learning habits. This educational challenge at basic design studios creates a severe need to study the reality of design education at foundation year and define appropriate educational methods with convenient project types with the intention of enhancing architecture education quality. Material for this study has been gathered through long-term direct observation at a first year second semester design studio at the faculty of architecture at EMU (known as FARC 102), fall and spring academic semester 2014-15. Distribution of a questionnaire among case study students and interviews with third and fourth design studio students who passed through the same methods of education in the past 2 years and conducting interviews with instructors are other methodologies used in this research. The results of this study reveal a risk of a mismatch between the implemented teaching method, project type and scale in this particular level and students’ learning styles. Although the existence of such risk due to varieties in students’ profiles could be expected to some extent, recommendations can support educators to reach maximum compatibility.

Keywords: architecture education, basic design studio, educational method, forms creation skill

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Authors: Kamyar Fakhr, Roozbeh Salmani

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Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

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Authors: Mengmeng Liu, J. David Frost

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Interstate highway system within the Atlanta Perimeter plays an important role in residents’ daily life. The serious influence of Atlanta I-85 Collapses implies that transportation system in the region lacks a cohesive and comprehensive transportation plan. Therefore, disaster resilience analysis of the transportation system is necessary. Resilience is the system’s capability to persist or to maintain transportation services when exposed to changes or shocks. This paper analyzed the resilience of the whole transportation system within the Perimeter and see how removing interstates within the Perimeter will affect the resilience of the transportation system. The data used in the paper are Atlanta transportation networks and LEHD Origin-Destination Employment Statistics data. First, we calculate the traffic flow on each road section based on LEHD data assuming each trip travel along the shortest travel time paths. Second, we calculate the measure of resilience, which is flow-based connectivity and centrality of the transportation network, and see how they will change if we remove each section of interstates from the current transportation system. Finally, we get the resilience function curve of the interstates and identify the most resilient interstates section. The resilience analysis results show that the framework of calculation resilience is effective and can provide some useful information for the transportation planning and sustainability analysis of the transportation infrastructures.

Keywords: connectivity, interstate highway system, network analysis, resilience analysis

Procedia PDF Downloads 261