Search results for: convolutional recurrent networks

Authors: Innocent Uzougbo Onwuegbuzie

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Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.

Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security

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Authors: Yanqun Li, Hong Geng

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The occurrence of Wenchuan earthquake in 2008 has led to severe damage to the rural areas of Chengdu city, such as the rupture of the social network, the stagnation of economic production and the rupture of living space. The post-disaster reconstruction has become a sustainable issue. As an important link to maintain the order of rural social development, social network should be an important content of post-disaster reconstruction. Therefore, this paper takes rural reconstruction communities in earthquake-stricken areas of Chengdu as the research object and adopts sociological research methods such as field survey, observation and interview to try to understand the transformation of rural social relations network under the influence of earthquake and its impact on rural space. It has found that rural societies under the earthquake generally experienced three phases: the break of stable social relations, the transition of temporary non-normal state, and the reorganization of social networks. The connotation of phased rural social relations also changed accordingly: turn to a new division of labor on the social orientation, turn to a capital flow and redistribution in new production mode on the capital orientation, and turn to relative decentralization after concentration on the spatial dimension. Along with such changes, rural areas have emerged some social issues such as the alienation of competition in the new industry division, the low social connection, the significant redistribution of capital, and the lack of public space. Based on a comprehensive review of these issues, this paper proposes the corresponding response mechanism. First of all, a reasonable division of labor should be established within the villages to realize diversified commodity supply. Secondly, the villages should adjust the industrial type to promote the equitable participation of capital allocation groups. Finally, external public spaces should be added to strengthen the field of social interaction within the communities.

Keywords: social relations, social support networks, industrial division, capital allocation, public space

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Authors: Usha Barahmand, Ruhollah Heydari Sheikh Ahmad, Sara Alaie Khoraem

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Introduction: The association of epilepsy with several psychological disorders and reduced quality of life has long been recognized. The present study aimed at comparing the personality profiles, quality of life and symptomatology of anxiety and depression in patients with epilepsy and healthy controls. Materials and Methods: Forty seven patients (29 men and 18 women) with diagnosed epilepsy participated in this study. Forty seven healthy controls who matched the patients in age and gender were also recruited. The participants’ personality and psychological profiles were assessed using the Depression, Anxiety, and Stress Scale (DASS-21), the Short-Form Health Survey (SF-36) and the HEXACO Personality Inventory (HEXACO-PI). Scoring algorithms were applied to the SF-36 produce the physical and mental component scores (PCS and MCS). Results: There were statistically significant differences in the total SF-36 score, anxiety, depression and stress scores of the DASS-21 between patients and controls. Anxiety, stress and depression scores significantly correlated inversely with the PCS and MCS. Data analysis showed that females had higher depression scores than males in both patients and controls, while males in both groups scored higher on stress. Patients’ personality scores were also different from those reported by controls on emotional, agreeableness and extroversion. Patients scored higher on emotionality, and lower on agreeableness and extraversion. Patients also scored lower on indices of quality of life. Regression analysis revealed that emotionality, anxiety, stress and MCS accounted for a significant proportion of the variance in severity of epileptic seizures. Conclusion: Stressful situations and psychological conditions as well as the personality trait of neuroticism were related to the occurrence of recurrent epileptic seizures.

Keywords: anxiety, depression, epilepsy, neuroticism, personality, quality of life, stress

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Authors: Lakmali Anthony, Bushra Oathman, Anshini Jain, Raaj Chandra

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Introduction: Abscesses are traditionally treated by incision and drainage with the packing of the residual abscess cavity until healing. This method requires regular visits from community nurses for continuous wound packing upon discharge from the hospital and causes considerable patient discomfort. Whether abscess cavity packing offers any advantage over non-packing has not yet been adequately studied to the best of our knowledge. This study aims to determine if there are differences in clinical outcomes of time to healing, fistula formation and recurrence of abscess between abscess cavity packing vs. non-packing groups. Methods: This study was a single-center, single-blind, randomized controlled trial where patients were randomized into packing and non-packing arms. All patients over 18 years presenting to Eastern Health with an abscess requiring incision and drainage in the theatre were invited to participate. Those with underlying conditions that cause recurrent abscesses were excluded. Data were collected from December 2018 to April 2020. Results: There were 63 patients who had abscesses treated with incision and drainage that were enrolled in the study, 52 of which were suitable for analysis. Demographic characteristics were similar in both groups. The packing group had a significantly longer time to heal compared to the non-packing group. Rates of fistula formation and recurrence of abscess were low and there were no statistically significant differences between groups. The packing group had more patients with delayed healing (defined as >60 days) and required more follow-up visits compared to the non-packing group. Conclusion: This pilot study indicates that abscesses can not only be managed safely with incision and drainage alone without the need for continuous abscess cavity packing but also that non-packing may offer clinical benefits to patients with earlier healing of abscesses compared to continuous cavity packing.

Keywords: abscess packing, subcutaneous, perianal, pilonidal

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Authors: Anita Chhatwal

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Purpose: The purpose of this paper is to evaluate and investigate the scope of usage of Academic Social Networking Websites (ASNs) by the Science faculty members across universities of North India, viz. Panjab University, Punjabi University and University of Delhi, Delhi. Design/Methodology/Approach: The present study is based upon the primary data collected from 81 science faculty participants from three universities of North India. Questionnaire method was used as an instrument for survey. The study is descriptive and research-based to investigate the popular ASNs amongst the participants from three sample universities and the purpose for which they use them along with the problems they encounter while using ASNs. Findings: The findings of the study revealed that majority of the participants were using ASNs for their academic needs. It was observed that majority of the participants (78%) used ASNs to access scientific papers, while 73.8% of the participants used them to share their research publications. ResearchGate (60.5%) and Google Scholar (59.7%) were the top two most preferred and widely used ASNs by the participants. The critical analysis of the data shows that laptops (86.3%) emerged as major tools for accessing ASNs. Shortage of computers was found to be the chief obstacle in accessing ASNs by the participants. Results of the study demonstrate that 56.3% of participants suggested conduct of seminars and training as the most effective method to increase the awareness of ASNs. Research Limitations/Implications: The study in hand absorbed the 81 faculty (Assistant Professors) members from 15 Science teaching departments across three sample universities of North India. The findings of this study will help the Government of India to regulate and simultaneously make effort to develop and enhance ASNs usage among faculty, researchers, and students. The present study will add to the existing library and information science literature and will be advantageous for all the information professionals as well. Originality/Value: This study is original survey based on primary data investigate the usage of ASNs by the academia. This study will be useful for research scholars, academicians and students all over the world.

Keywords: academic social networks, awareness and usage, North India, scholarly communication, web 2.0

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Authors: M. Hussain, Aqsa Farooq

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Let G = (V,E) be a connected graph and distance between any two vertices a and b in G is a−b geodesic and is denoted by d(a, b). A set of vertices W resolves a graph G if each vertex is uniquely determined by its vector of distances to the vertices in W. A metric dimension of G is the minimum cardinality of a resolving set of G. In this paper line graph of honeycomb network has been derived and then we calculated the metric dimension on line graph of honeycomb network.

Keywords: Resolving set, Metric dimension, Honeycomb network, Line graph

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Authors: Carole Salis, Marie F. Wilson, Fabrizio Murgia, Cristian Lai, Franco Atzori, Giulia M. Orrù

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ANDASA is a knowledge management platform for the capitalization of knowledge and cultural assets for the artistic and cultural sectors. It was built based on the priorities expressed by the participating artists. Through mapping artistic activities and specificities, it enables to highlight various aspects of the artistic research and production. Such instrument will contribute to create networks and partnerships, as it enables to evidentiate who does what, in what field, using which methodology. The platform is accessible to network participants and to the general public.

Keywords: cultural promotion, knowledge representation, cultural maping, ICT

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Authors: Hamida Memon, Muhammad Sanan

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A 34-year-old male with no prior health issues presented with a wound in his left leg exhibiting active pus discharge, intense inflammation, pain radiating from the buttocks to the knee, foot drop, and skin darkening. Four years prior, he sustained an untreated dislocation of the hip joint and acetabulum from a road traffic accident. Initial nerve conduction studies (NCS) and electromyography (EMG) revealed severe axonotomesis of the left sciatic nerve and reduced compound muscle action potential in the left common peroneal nerve. Despite normal venous flow, edema and cellulitis were noted. Follow-up NCS/EMG in 2022 showed improvement, but in 2023, the patient experienced recurrent infection and underwent surgical intervention with tissue culture. Postoperative care included antibiotics and pain management. NCS/EMG in 2024 indicated decreased nerve amplitudes and conduction velocities, consistent with moderate axonotmesis and ongoing recovery, alongside incidental right S1 radiculopathy. General lab tests and abdominal imaging were normal. The patient was treated with Pregabalin and Neurobion for neuropathic pain and nerve support and is currently under observation by a tertiary sector hospital for treatment. This case underscores the critical importance of prompt treatment for hip dislocations to prevent long-term complications such as neuropathy and avascular necrosis. Delays in treatment significantly increase the risk of severe outcomes, highlighting the need for timely intervention. Overall, the case illustrates the challenges of managing complex nerve injuries and the importance of comprehensive care for optimal recovery.

Keywords: sciatic nerve neuropathy, hip dislocation, acetabular fracture, radiculopathy

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Authors: Abdullah A. Al Orainy

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Small cell backhaul solutions need to be cost-effective, scalable, and easy to install. This paper presents an overview of small cell backhaul technologies. Wireless solutions including TV white space, satellite, sub-6 GHz radio wave, microwave and mmWave with their backhaul characteristics are discussed. Recent research on issues like beamforming, backhaul architecture, precoding and large antenna arrays, and energy efficiency for dense small cell backhaul with mmWave communications is reviewed. Recent trials of 5G technologies are summarized.

Keywords: backhaul, small cells, wireless, 5G

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Authors: Joy Cao, Min Zhou

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Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: J. L. Oliver, T. Agryzkov, L. Tortosa, J. Vicent, J. Santacruz

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This paper aims to demonstrate how the use of Network Theory can be applied to a very interesting and complex urban situation: The parts of a city which may have some patrimonial value, but because of their lack of relevant architectural elements, they are not considered to be historic in a conventional sense. In this paper, we use the suburb of La Villaflora in the city of Quito, Ecuador as our case study. We first propose a system of indicators as a tool to characterize and quantify the historic value of a geographic area. Then, we apply these indicators to the suburb of La Villaflora and use Network Theory to understand and propose actions.

Keywords: graphs, mathematics, networks, urban studies

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Authors: Animish Jain

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This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: Sabah Khan

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The idea of universal Islam tends to exaggerate the extent of homogeneity in Islamic beliefs and practices across Muslim communities. In the age of migration, various Muslim communities are in diaspora. The immediate implication of this is what happens to Islam in diaspora? How Islam gets represented in new forms? Such pertinent questions need to be dealt with. This paper shall draw on the idea of religious transnationalism, primarily transnational Islam. There are multiple ways to conceptualize transnational phenomenon with reference to Islam in terms of flow of people, transnational organizations and networks; Ummah oriented solidarity and the new Muslim public sphere. This paper specifically deals with the new Muslim public sphere. It primarily refers to the space and networks enabled by new media and communication technologies, whereby Muslim identity and Islamic normativity are rehearsed, debated by people in different locales. A new sense of public is emerging across Muslim communities, which needs to be contextualized. This paper uses both primary and secondary data. Primary data elicited through content analysis of audio-visuals on social media and secondary sources of information ranging from books, articles, journals, etc. The basic aim of the paper is to focus on the emerging Muslim public sphere and the role of media in expanding public spheres of Islam. It also explores how Muslims in diaspora negotiate Islam and Islamic practices through media and the new Muslim public sphere. This paper cogently weaves in discussions firstly, of re-intellectualization of Islamic discourse in the public sphere. In other words, how Muslims have come to reimagine their collective identity and critically look at fundamental principles and authoritative tradition. Secondly, the emerging alternative forms of Islam by young Muslims in diaspora. In other words, how young Muslims search for unorthodox ways and media for religious articulation, including music, clothing and TV. This includes transmission and distribution of Islam in diaspora in terms of emerging ‘media Islam’ or ‘soundbite Islam’. The new Muslim public sphere has offered an arena to a large number of participants to critically engage with Islam, which leads not only to a critical engagement with traditional forms of Islamic authority but also emerging alternative forms of Islam and Islamic practices.

Keywords: Islam, media, Muslims, public sphere

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Authors: Somayeh Pashaee

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The ever-increasing growth of the Internet and the development of information and communication technology have prompted the politicians of different countries to use virtual networks as an efficient tool for their foreign policy. The communication of governments and countries, even in the farthest places from each other, through electronic networks, has caused vast changes in the way of statecraft and governance. Importantly, in the meantime, diplomacy, which is always based on information and communication, has been affected by the new prevailing conditions and new technologies more than other areas and has faced greater changes. The emergence of virtual space and the formation of new communication tools in the field of public diplomacy has led to the redefinition of the framework of diplomacy and politics in the international arena and the appearance of a new aspect of diplomacy called digital diplomacy. Digital diplomacy is in the concept of changing relations from a face-to-face and traditional way to a non-face-to-face and new way, and its purpose is to solve foreign policy issues using virtual space. Digital diplomacy, by affecting diplomatic procedures and its change, explains the role of technology in the visualization and implementation of diplomacy in different ways. The purpose of this paper is to investigate the position of digital diplomacy in the public diplomacy of the Islamic Republic of Iran. The paper tries to answer these two questions in a descriptive-analytical way, considering the progress of communication and the role of virtual space in the service of diplomacy, what is the approach of the Islamic Republic of Iran towards digital diplomacy and the use of a new way of establishing foreign relations in public diplomacy? What capacities and damages are facing the country after the use of this type of new diplomacy? In this paper, various theoretical concepts in the field of public diplomacy and modern diplomacy, including Geoff Berridge, Charles Kegley, Hans Tuch and Ronald Peter Barston, as well as the theoretical framework of Marcus Holmes on digital diplomacy, will be used as a conceptual basis to support the analysis. As a result, in order to better achieve the political goals of the country, especially in foreign policy, the approach of the Islamic Republic of Iran to public diplomacy with a focus on digital diplomacy should be strengthened and revised. Today, only emphasizing on advancing diplomacy through traditional methods may weaken Iran's position in the public opinion level from other countries.

Keywords: digital diplomacy, public diplomacy, islamic republic of Iran, foreign policy, opportunities and challenges

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Authors: Xiping Wang，Shuran Yao, Liqin Dai

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Many studies report the winter is getting warmer and the minimum air temperature is obviously rising as the important climate warming evidences. The exacerbated air temperature fluctuation tending to bring more severe weather variation is another important consequence of recent climate change which induced more disasters to crop growth in quite a certain regions. Hebei Province is an important winter wheat growing province in North of China that recently endures more winter freezing injury influencing the local winter wheat crop management. A winter wheat freezing injury assessment Bayesian Network framework was established for the objectives of estimating, assessing and predicting winter wheat freezing disasters in Hebei Province. In this framework, the freezing disasters was classified as three severity degrees (SI) among all the three types of freezing, i.e., freezing caused by severe cold in anytime in the winter, long extremely cold duration in the winter and freeze-after-thaw in early season after winter. The factors influencing winter wheat freezing SI include time of freezing occurrence, growth status of seedlings, soil moisture, winter wheat variety, the longitude of target region and, the most variable climate factors. The climate factors included in this framework are daily mean and range of air temperature, extreme minimum temperature and number of days during a severe cold weather process, the number of days with the temperature lower than the critical temperature values, accumulated negative temperature in a potential freezing event. The Bayesian Network model was evaluated using actual weather data and crop records at selected sites in Hebei Province using real data. With the multi-stage influences from the various factors, the forecast and assessment of the event-based target variables, freezing injury occurrence and its damage to winter wheat production, were shown better scoped by Bayesian Network model.

Keywords: bayesian networks, climatic change, freezing Injury, winter wheat

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: C. Slim

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This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.

Keywords: Artificial Neural Networks (ANN), Support vector machine (SVM), Data Envelopment Analysis (DEA), Aggregations, indicators of performance

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Authors: Li Feng

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In IEEE 802.11 networks, it is well known that the traditional time-domain contention often leads to low channel utilization. The first frequency-domain contention scheme, the time to frequency (T2F), has recently been proposed to improve the channel utilization and has attracted a great deal of attention. In this paper, we survey the latest research progress on the weighed frequency-domain contention. We present the basic ideas, work principles of these related schemes and point out their differences. This paper is very useful for further study on frequency-domain contention.

Keywords: 802.11, wireless LANs, frequency-domain contention, T2F

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Authors: Muhammad Dawood Idrees, Maria Hafeez, Arsalan Ansari

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Toll tax collection is the earliest method of tax collection and revenue generation. This revenue is utilized for the development of roads networks, maintenance, and connecting to roads and highways across the country. Pakistan is one of the biggest countries, covers a wide area of land, roads networks, and motorways are important source of connecting cities. Every day millions of people use motorways, and they have to stop at toll plazas to pay toll tax as majority of toll plazas are manually collecting toll tax. The purpose of this study is to calculate the waiting time of vehicles at Karachi Hyderabad (M-9) motorway. As Karachi is the biggest city of Pakistan and hundreds of thousands of people use this route to approach other cities. Currently, toll tax collection is manual system which is a major cause for long time waiting at toll plaza. This study calculates the waiting time of vehicles, fuel consumed in waiting time, manpower employed at toll plaza as all process is manual, and it also leads to mental and physical fatigue of driver. All wastages of sources are also calculated, and a most feasible automatic toll tax collection system is proposed which is not only beneficial to reduce waiting time but also beneficial in reduction of fuel, reduction of manpower employed, and reduction in physical and mental fatigue. A cost comparison in terms of wastages is also shown between manual and automatic toll tax collection system (E-Z Pass). Results of this study reveal that, if automatic tool collection system is implemented at Karachi to Hyderabad motorway (M-9), there will be a significance reduction in waiting time of vehicles, which leads to reduction of fuel consumption, environmental pollution, mental and physical fatigue of driver. All these reductions are also calculated in terms of money (Pakistani rupees) and it is obtained that millions of rupees can be saved by using automatic tool collection system which will lead to improve the economy of country.

Keywords: toll tax collection, waiting time, wastages, driver fatigue

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Authors: Atiya Khan

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Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

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Authors: Andreev V. A., Kovalenko T. N., Privolnev V. V., Chernavin A. V., Knyazeva E. R.

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Aim: To evaluate the antagonistic activity of Streptococcus salivarius K12 (SsK12) against ENT and oral cavity infection pathogens (S. pneumoniae, S. pyogenes, S. aureus), gram-negative bacteria (E. coli, P. aeruginosa) and C. albicans. Materials and methods: The probiotic strain SsK12 was isolated from the dietary supplement containing at least 1 × 109 CFU per tablet. The tablet was dissolved in the enrichment broth. The resulting suspension was seeded on 5% blood agar and incubated at 35°C in 4-6% CO2 for 48 hours. The raised culture was identified as Streptococcus salivarius with MALDI-TOF mass spectrometry method. The evaluation of SsK12 antagonistic activity was carried out using a perpendicular streak technique. The daily SsK12 culture was inoculated as heavy streaks with a loop at one side of Petri dish with the Muller-Hinton agar (MHA) and incubated for 24 hours at 350 C in anaerobic conditions. It was supposed that bacteriocins would diffuse over the whole area of the agar media. On the next day S. pneumoniae, S. pyogenes, S. aureus, E. coli, P. aeruginosa and C. albicans clinical isolates were streaked at the clear side of MHA Petri dish. MHA Petri dish inoculated with SsK12 (one part) and with the respective clinical isolates (another part) streaked perpendicularly on the same day was used as the control. Results: There was no growth of S. pyogenes on the Petri dish with SsK12 daily culture; the growth of a few colonies of S. pneumonia was noted. The growth of S. aureus, E. coli, P. aeruginosa and C. albicans was noted along the inoculated streak. On the control Petri dish with simultaneous inoculating of the SsK12 strain and the test cultures, the growth of all the testes isolates was noted. Conclusions: (1) SsK12 possesses perfect antagonistic activity against S. pyogenes and good activity against S. pneumoniae. (2) There was no antagonistic activity of SsK12 against S. aureus, E. coli, P. aeruginosa and C. albicans. (3) SsK12 antagonistic properties make it possible to use this probiotic strain for prophylaxis of recurrent ENT infections.

Keywords: probiotics, SsK12, streptococcus salivarius K12, antagonistic activity

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Authors: Hardisiswo Soedjana, Inne Caroline

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Deep dermal or full thickness burns are inevitably lead to post-burn contractures. These contractures remain to be one of the most concerning late complications of burn injuries. Surgical management includes releasing the contracture followed by resurfacing the defect accompanied by post-operative rehabilitation. Optimal treatment of post-burn contractures depends on the characteristics of the contractures. This study is aimed to describe clinical characteristics, problems, and management of post-burn contractures in adults and children. A retrospective analysis was conducted from medical records of patients suffered from contractures after burn injuries admitted to Hasan Sadikin general hospital between January 2016 and January 2018. A total of 50 patients with post burn contractures were included in the study. There were 17 adults and 33 children. Most patients were male, whose age range within 15-59 years old and 5-9 years old. Educational background was mostly senior high school among adults, while there was only one third of children who have entered school. Etiology of burns was predominantly flame in adults (82.3%); whereas flame and scald were the leading cause of burn injury in children (11%). Based on anatomical regions, hands were the most common affected both in adults (35.2%) and children (48.5%). Contractures were identified in 6-12 months since the initial burns. Most post-burn hand contractures were resurfaced with full-thickness skin graft (FTSG) both in adults and children. There were 11 patients who presented with recurrent contracture after previous history of contracture release. Post-operative rehabilitation was conducted for all patients; however, it is important to highlight that it is still challenging to control splinting and exercise when patients are discharged and especially the compliance in children. In order to improve quality of life in patients with history of deep burn injuries, prevention of contractures should begin right after acute care has been established. Education for the importance of splinting and exercise should be administered as comprehensible as possible for adult patients and parents of pediatric patients.

Keywords: burn, contracture, education, exercise, splinting

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Authors: Sitarrine Thongpussawal, Dasarath Jayasuriya, Thanaroj Woraratprasert, Sakawtree Prajamwong

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Thailand grapples with recurrent floods causing substantial repercussions on its economy, society, and environment. In 2021, the economic toll of these floods amounted to an estimated 53,282 million baht, primarily impacting the agricultural sector. The existing flood monitoring system in Thailand suffers from inaccuracies and insufficient information, resulting in delayed warnings and ineffective communication to the public. The Office of the National Water Resources (OWNR) is tasked with developing and integrating data and information systems for efficient water resources management, yet faces challenges in monitoring accuracy, forecasting, and timely warnings. This study endeavors to evaluate the viability of enhancing Thailand's Flood Forecasting and Warning (FFW) systems. Additionally, it aims to formulate a comprehensive work package grounded in international best practices to enhance the country's FFW systems. Employing qualitative research methodologies, the study conducted in-depth interviews and focus groups with pertinent agencies. Data analysis involved techniques like note-taking and document analysis. The study substantiates the feasibility of developing and enhancing FFW systems in Thailand. Implementation of international best practices can augment the precision of flood forecasting and warning systems, empowering local agencies and residents in high-risk areas to prepare proactively, thereby minimizing the adverse impact of floods on lives and property. This research underscores that Thailand can feasibly advance its FFW systems by adopting international best practices, enhancing accuracy, and improving preparedness. Consequently, the study enriches the theoretical understanding of flood forecasting and warning systems and furnishes valuable recommendations for their enhancement in Thailand.

Keywords: flooding, forecasting, warning, monitoring, communication, Thailand

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Authors: Emma J. Dale, Christina D. Buesching, Kevin R. Theis, David W. Macdonald

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This study investigates the oral and intestinal microbiomes of wild-living European badgers (Meles meles) and will relate inter-individual differences to social contact networks, somatic and reproductive fitness, varying susceptibility to bovine tuberculous (bTB) and to the olfactory advertisement. Badgers are an interesting model for this research, as they have great variation in body condition, despite living in complex social networks and having access to the same resources. This variation in somatic fitness, in turn, affects breeding success, particularly in females. We postulate that microbiota have a central role to play in determining the successfulness of an individual. Our preliminary results, characterising the microbiota of individual badgers, indicate unique compositions of microbiota communities within social groups of badgers. This basal information will inform further questions related to the extent microbiota influence fitness. Hitherto, the potential role of microbiota has not been considered in determining host condition, but also other key fitness variables, namely; communication and resistance to disease. Badgers deposit their faeces in communal latrines, which play an important role in olfactory communication. Odour profiles of anal and subcaudal gland secretions are highly individual-specific and encode information about group-membership and fitness-relevant parameters, and their chemical composition is strongly dependent on symbiotic microbiota. As badgers sniff/ lick (using their Vomeronasal organ) and over-mark faecal deposits of conspecifics, these microbial communities can be expected to vary with social contact networks. However, this is particularly important in the context of bTB, where badgers are assumed to transmit bTB to cattle as well as conspecifics. Interestingly, we have found that some individuals are more susceptible to bTB than are others. As acquired immunity and thus potential susceptibility to infectious diseases are known to depend also on symbiotic microbiota in other members of the mustelids, a role of particularly oral microbiota can currently not be ruled out as a potential explanation for inter-individual differences in infection susceptibility of bTB in badgers. Tri annually badgers are caught in the context of a long-term population study that began in 1987. As all badgers receive an individual tattoo upon first capture, age, natal as well as previous and current social group-membership and other life history parameters are known for all animals. Swabs (subcaudal ‘scent gland’, anal, genital, nose, mouth and ear) and fecal samples will be taken from all individuals, stored at -80oC until processing. Microbial samples will be processed and identified at Wayne State University’s Theis (Host-Microbe Interactions) Lab, using High Throughput Sequencing (16S rRNA-encoding gene amplification and sequencing). Acknowledgments: Gas-Chromatography/ Mass-spectrometry (in the context of olfactory communication) analyses will be performed through an established collaboration with Dr. Veronica Tinnesand at Telemark University, Norway.

Keywords: communication, energetics, fitness, free-ranging animals, immunology

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Authors: Nazira B. Bekenova, Lydia A. Mukovozova, Andrej M. Grjibovski, Alma Z. Tokayeva, Yerbol M. Smail, Nurlan E. Aukenov

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Erysipelas is an infectious disease with socio-economic significance and prone to prolonged recurrent course (30%). Contribution of genetic factors, in particular the gene polymorphism of cytokines, can be essential in disease etiology and pathogenesis. Interleukin – 17 A are produced by T helpers of 17 type and plays a key role in development of local inflammation process. Local inflammatory process is a dominant in the clinic of erysipelas. Established that the skin and mucosas are primary areas of migration (homing) Th17-cell and their cytokines are stimulate the barrier function of the epithelium. We studied associations between gene polymorphism of IL-17A (C737T) rs 8193036 and IL-17A level in patients with erysipelas Kazakh population. Altogether, 90 cases with erysipelas and 90 healthy controls from an ethnic Kazakh population comprised the sample. Cases were identified at Clinical Infectious Diseases Hospital of Semey (Kazakhstan). The IL-17A (rs8193036) polymorphism was analyzed by a real time polymerase chain reaction. Plasma levels of IL-17 A were assessed by immuneenzyme analysis method using ‘Vector-Best’ test-system (Russia). Differences in levels of IL-17 A between CC, TT, CT groups were studied using Kruskal — Wallis test. Pairwise comparisons were performed using Mann-Whitney tests with Bonferroni correction (New significance level was set to 0.025). We found, that in patients with erysipelas with CC genotype the level of IL-17 A was higher (p= 0, 010) compared to the carriers of CT genotype. When compared the level of IL – 17 A between the patients with TT genotype and patients with CC genotype, also between the patients with CT genotype and patients with TT genotype statistically significant differences are not revealed (p = 0.374 and p = 0.043, respectively). Comparisons of IL-17 A plasma levels between the CC and CT genotypes, between the CC and TT genotypes, and between the TT and CT in healthy patients did not reveal significant differences (p = 0, 291). Therefore, we are determined the associations of gene polymorphism of IL-17 A (C737T) with its level in patients erysipelas carriers CC genotype.

Keywords: erysipelas, interleukin – 17 A, Kazakh, polymorphism

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Authors: Rob van den Dam

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Today’s Internet of Things (IoT) comprises more than a billion intelligent devices, connected via wired/wireless communications. The expected proliferation of hundreds of billions more places us at the threshold of a transformation sweeping across the communications industry. Yet, we found that the IoT architecture and solutions that currently work for billions of devices won’t necessarily scale to tomorrow’s hundreds of billions of devices because of high cost, lack of privacy, not future-proof, lack of functional value and broken business models. As the IoT scales exponentially, decentralized networks have the potential to reduce infrastructure and maintenance costs to manufacturers. Decentralization also promises increased robustness by removing single points of failure that could exist in traditional centralized networks. By shifting the power in the network from the center to the edges, devices gain greater autonomy and can become points of transactions and economic value creation for owners and users. To validate the underlying technology vision, IBM jointly developed with Samsung Electronics the autonomous decentralized peer-to- peer proof-of-concept (PoC). The primary objective of this PoC was to establish a foundation on which to demonstrate several capabilities that are fundamental to building a decentralized IoT. Though many commercial systems in the future will exist as hybrid centralized-decentralized models, the PoC demonstrated a fully distributed proof. The PoC (a) validated the future vision for decentralized systems to extensively augment today’s centralized solutions, (b) demonstrated foundational IoT tasks without the use of centralized control, (c) proved that empowered devices can engage autonomously in marketplace transactions. The PoC opens the door for the communications and electronics industry to further explore the challenges and opportunities of potential hybrid models that can address the complexity and variety of requirements posed by the internet that continues to scale. Contents: (a) The new approach for an IoT that will be secure and scalable, (b) The three foundational technologies that are key for the future IoT, (c) The related business models and user experiences, (d) How such an IoT will create an 'Economy of Things', (e) The role of users, devices, and industries in the IoT future, (f) The winners in the IoT economy.

Keywords: IoT, internet, wired, wireless

Procedia PDF Downloads 333