Search results for: biocatalytic approaches

Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: Meghana Shankara, Priyadarshini Natarajan

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Infrared (IR) spectroscopy has revolutionized the way we look at materials around us. Unraveling the pattern in the molecular spectra of materials to analyze the composition and properties of it has been one of the most interesting challenges in modern science. Applications of the IR spectrometry are numerous in the field’s pharmaceuticals, health, food and nutrition, oils, agriculture, construction, polymers, beverage, fabrics and much more limited only by the curiosity of the people. Near Infrared (NIR) spectrometry is applied robustly in analyzing the solids and liquid substances because of its non-destructive analysis method. In this paper, we have reviewed the application of NIR spectrometry in milk quality analysis and have presented the modes of measurement applied in NIRS measurement setup, Design of Experiment (DoE), classification/quantification algorithms used in the case of milk composition prediction like Fat%, Protein%, Lactose%, Solids Not Fat (SNF%) along with different approaches for adulterant identification. We have also discussed the important NIR ranges for the chosen milk parameters. The performance metrics used in the comparison of the various Chemometric approaches include Root Mean Square Error (RMSE), R^2, slope, offset, sensitivity, specificity and accuracy

Keywords: chemometrics, design of experiment, milk quality analysis, NIRS measurement modes

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Authors: Walid Hassairi, Moncef Bousselmi, Mohamed Abid

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Functional verification is a major part of today’s system design task. Several approaches are available for verification on a high abstraction level, where designs are often modeled using MATLAB/Simulink. However, different approaches are a barrier to a unified verification flow. In this paper, we propose a co-simulation interface between SystemC and MATLAB and Simulink to enable functional verification of multi-abstraction levels designs. The resulting verification flow is tested on JPEG compression algorithm. The required synchronization of both simulation environments, as well as data type conversion is solved using the proposed co-simulation flow. We divided into two encoder jpeg parts. First implemented in SystemC which is the DCT is representing the HW part. Second, consisted of quantization and entropy encoding which is implemented in Matlab is the SW part. For communication and synchronization between these two parts we use S-Function and engine in Simulink matlab. With this research premise, this study introduces a new implementation of a Hardware SystemC of DCT. We compare the result of our simulation compared to SW / SW. We observe a reduction in simulation time you have 88.15% in JPEG and the design efficiency of the supply design is 90% in SDR.

Keywords: hardware/software, co-design, co-simulation, systemc, matlab, s-function, communication, synchronization

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Authors: Sumalee Tientongdee

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In this study, it was aimed to investigate Physics achievement of the pre-service science teacher studying in general science program at Suan Sunandha Rajabhat University, Bangkok, Thailand. The program has provided the new curriculum that focuses on 21st-century skills development. Active learning approaches are used to teach in all subjects. One of the active learning approaches Peer Instruction, or PI was used in this study to teach physics of waves as a compulsory course. It was conducted in the second semester from January to May of 2017. The concept test was given to evaluate pre-service science teachers’ understanding in concept of waves. Problem-solving assessment form was used to evaluate their problem-solving skill. The results indicated that after they had learned through Peer Instruction in physics of waves course, their concepts in physics of waves was significantly higher at 0.05 confident levels. Their problem-solving skill from the whole class was at the highest level. Based on the group interview on the opinions of using Peer Instruction in Physics class, they mostly felt that it was very useful and helping them understand more about physics, especially for female students.

Keywords: peer instruction, physics of waves, pre-service science teacher, Suan Sunandha Rajabhat university

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Authors: Antonella Regueiro Fernandez

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This paper examines the issue of period poverty and the innovative approaches – or lack thereof – that national systems are using to tackle the issue. Through a systems-thinking and economical approach, the paper analyzes the intricate relationship between proper systemic change and sustainable innovations for this global problem. The first part of the research introduces period poverty and the lack of sustainable options currently in place to resolve the issue. The second part delves into a comparison of existing technologies – single-use and reusable period products -- and their benefits and deficiencies. It also provides a comparison of two countries and their existing solutions landscape (Scotland and the United States), arguing that while Scotland has provided an innovative national solution to the problem, it still lacks a proper assessment of the issue of sustainability, while the United States continues to lag in offering any holistic solution at all. The last part provides a conclusion to the research and affirms the importance of holistic policymaking approaches to issues of period poverty, which have the potential to truly benefit half of the world’s population while also encouraging environmental preservation.

Keywords: gender equity, sustainability, period poverty, SDGs, sustainable development

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Hamed Hossein Afshari, Shahrzad Jalali, Amir Hossein Ghods, Bijan Raahemi

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This paper introduces an automated clustering solution that applies to WiFi/Bluetooth sensing data and is later used for traffic management applications. The paper initially summarizes a number of clustering approaches and thereafter shows their performance for noise removal. In this context, clustering is used to recognize WiFi and Bluetooth MAC addresses that belong to passengers traveling by a public urban transit bus. The main objective is to build an intelligent system that automatically filters out MAC addresses that belong to persons located outside the bus for different routes in the city of Ottawa. The proposed intelligent system alleviates the need for defining restrictive thresholds that however reduces the accuracy as well as the range of applicability of the solution for different routes. This paper moreover discusses the performance benefits of the presented clustering approaches in terms of the accuracy, time and space complexity, and the ease of use. Note that results of clustering can further be used for the purpose of the origin-destination estimation of individual passengers, predicting the traffic load, and intelligent management of urban bus schedules.

Keywords: WiFi-Bluetooth sensing, cluster analysis, artificial intelligence, traffic management

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Authors: Pratham Madnur, Prathamkumar Shetty, Sneha Varur, Gouri Parashetti

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In order to overcome conventional obstacles, this research paper investigates novel approaches for cricket pitch and ball detection that make use of cutting-edge technologies. The research integrates OpenCV for pitch inspection and modifies the YOLOv8 model for cricket ball detection in order to overcome the shortcomings of manual pitch assessment and traditional ball detection techniques. To ensure flexibility in a range of pitch environments, the pitch detection method leverages OpenCV’s color space transformation, contour extraction, and accurate color range defining features. Regarding ball detection, the YOLOv8 model emphasizes the preservation of minor object details to improve accuracy and is specifically trained to the unique properties of cricket balls. The methods are more reliable because of the careful preparation of the datasets, which include novel ball and pitch information. These cutting-edge methods not only improve cricket analytics but also set the stage for flexible methods in more general sports technology applications.

Keywords: OpenCV, YOLOv8, cricket, custom dataset, computer vision, sports

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Authors: Cecil Blake, Tolu Kayode-Adedeji, Innocent Chiluwa, Charles Iruonagbe

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National, regional and international security threats have dominated the twenty-first century thus far. Insurgencies that utilize “terrorism” as their primary strategy pose the most serious threat to global security. States in turn adopt terrorist strategies to resist and even defeat insurgents who invoke the legitimacy of statehood to justify their action. In short, the era is dominated by the use of terror tactics by state and non-state actors. Globally, there is a powerful network of groups involved in insurgencies using Islam as the bastion for their cause. In Africa, there are Boko Haram, Al Shabaab and Al Qaeda in the Maghreb representing Islamic groups utilizing terror strategies and tactics to prosecute their wars. The task at hand is to discover and to use multiple ways of handling the present security threats, including novel approaches to policy formulation, implementation, monitoring and evaluation that would pay significant attention to the important role of culture and communication strategies germane for discursive means of conflict resolution. In other to achieve this, the proposed research would address inter alia, root causes of insurgences that predicate their mission on Islamic tenets particularly in Africa; discursive and non-discursive counter-terrorism approaches fashioned by African governments, continental supra-national and regional organizations, recruitment strategies by major non-sate actors in Africa that rely solely on terrorist strategies and tactics and sources of finances for the groups under study. A major anticipated outcome of this research is a contribution to answers that would lead to the much needed stability required for development in African countries experiencing insurgencies carried out by the use of patterned terror strategies and tactics. The nature of the research requires the use of triangulation as the methodological tool.

Keywords: counter-terrorism, discourse, Nigeria, security, terrorism

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Authors: H. Chassaigne, S. Gioria, J. Lobo Vicente, D. Carpi, P. Barboro, G. Tomasi, A. Kinsner-Ovaskainen, F. Rossi

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Emerging approaches in the area of exposure to nanomaterials and assessment of human health effects combine the use of in vitro systems and analytical techniques to study the perturbation of the proteome and/or the metabolome. We investigated the modification in the cytoplasmic compartment of the Balb/3T3 cell line exposed to gold nanoparticles. On one hand, the proteomic approach is quite standardized even if it requires precautions when dealing with in vitro systems. On the other hand, metabolomic analysis is challenging due to the chemical diversity of cellular metabolites that complicate data elaboration and interpretation. Differentially expressed proteins were found to cover a range of functions including stress response, cell metabolism, cell growth and cytoskeleton organization. In addition, de-regulated metabolites were annotated using the HMDB database. The "omics" fields hold huge promises in the interaction of nanoparticles with biological systems. The combination of proteomics and metabolomics data is possible however challenging.

Keywords: data processing, gold nanoparticles, in vitro systems, metabolomics, proteomics

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Authors: Deepshikha Shukla, C. H. Solanki, Mayank K. Desai

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Amongst all the natural hazards, earthquakes have the potential for causing the greatest damages. Since the earthquake forces are random in nature and unpredictable, the quantification of the hazards becomes important in order to assess the hazards. The time and place of a future earthquake are both uncertain. Since earthquakes can neither be prevented nor be predicted, engineers have to design and construct in such a way, that the damage to life and property are minimized. Seismic hazard analysis plays an important role in earthquake design structures by providing a rational value of input parameter. In this paper, both mathematical, as well as computational methods adopted by researchers globally in the past five years, will be discussed. Some mathematical approaches involving the concepts of Poisson’s ratio, Convex Set Theory, Empirical Green’s Function, Bayesian probability estimation applied for seismic hazard and FOSM (first-order second-moment) algorithm methods will be discussed. Computational approaches and numerical model SSIFiBo developed in MATLAB to study dynamic soil-structure interaction problem is discussed in this paper. The GIS-based tool will also be discussed which is predominantly used in the assessment of seismic hazards.

Keywords: computational methods, MATLAB, seismic hazard, seismic measurements

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Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

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Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

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The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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Authors: Yujie Zhang

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There are debates around the legitimacy of capital punishment, i.e., whether death could serve as a proper execution in our legal system or not. Different arguments have been raised. However, none of them seem able to provide a determined answer to the issue; this results in a lack of instruction in the legal practice. This article, therefore, devotes itself to the effort to find such an answer. It takes the perspective of rights, through interpreting the concept of right to life, which capital punishment appears to be in confliction with in the two traditional approaches, to reveal a possibly best account of the right and its conclusion on capital punishment. However, this effort is not a normative one which focuses on what ought to be. It means the article does not try to work out which argument we should choose and solve the hot debate on whether capital punishment should be allowed or not. It, again, does not propose which perspective we should take to approach this issue or generally which account of right must be better; rather, it is more a thought experiment. It attempts to raise a new perspective to approach the issue of the legitimacy of capital punishment. Both its perspective and conclusion therefore are tentative: what if we view this issue in a way we have never tried before, for example the different accounts of right to life? In this sense, the perspective could be defied, while the conclusion could be rejected. Other perspectives and conclusions are also possible. Notwithstanding, this tentative perspective and account of the right still could not be denied from serving as a potential approach, since it does have the ability to provide us with a determined attitude toward capital punishment that is hard to achieve through existing arguments.

Keywords: capital punishment, right to life, theories of rights, the choice theory

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Authors: Zahra R. Almansoor

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Background: Selective serotonin reuptake inhibitors (SSRI’s) and cognitive behavioural therapy (CBT) are the main treatment methods used for patients with obsessive compulsive disorder (OCD) under the National Institute of Health and Care Excellence (NICE) guidelines. Yet many patients are left with residual symptoms or remit, so several other therapeutic approaches have been explored. Objective: The objective was to systematically review the available literature regarding the treatment efficacy of current and potential approaches and diagnostic strategies. Method: First, studies were examined concerning diagnosis, prognosis, and influencing factors. Then, one reviewer conducted a systematic search of six databases using stringent search terms. Results of studies exploring the efficacy of treatment interventions were analysed and compared separately for adults and children. This review was limited to randomised controlled trials (RCT’s) conducted from 2016 onwards, and an improved Y-BOCS (Yale- Brown obsessive compulsive scale) score was the primary outcome measure. Results: Technology-based interventions including internet-based cognitive behavioural therapy (iCBT) were deemed as potentially effective. Discrepancy remains about the benefits of SSRI use past one year, but potential medication adjuncts include amantadine. Treatments such as association splitting and family and mindfulness strategies also have future potential. Conclusion: A range of potential therapies exist, either as treatment adjuncts to current interventions or as sole therapies. To further improve efficacy, it may be necessary to remodel the current NICE stepped-care model, especially regarding the potential use of lower intensity, cheaper treatments, including iCBT. Although many interventions show promise, further research is warranted to confirm this.

Keywords: family and group treatment, mindfulness strategies, novel treatment approaches, standard treatment, technology-based interventions

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Authors: Jacques C. Duvenhage

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The use of emoticons or so-called ‘emojis’ has gained much attention, not only in the daily use thereof with friends or family but also within the workplace amongst co-workers and employers. Even though emojis may be seen as a way to express feelings or even ideas, it may present legal challenges in the workplace. With new emojis being created on a daily basis, communicating through emojis, whether via phone, email or social media platforms, can become convoluted, especially within the working environment. The question to be addressed is how and/or whether Australian legislators will regulate the use of emojis (as a form of technology) in the workplace to prevent harassment, discrimination and other forms of prejudice. The emojis sent to co-workers may be interpreted by employees and even employers in different ways depending on their age, sexual orientation, and cultural background. Therefore, Australian courts will need to interpret an emoji’s meaning on a case-by-case basis. This paper will explore the use of emojis in the workplace (drawing on a desktop study), the impact emojis have on the employer-employee relationship as well as co-worker relationships, its legal application through case studies and whether a legal framework should be adopted by Australian legislators on this issue. Furthermore, this paper will reflect on the legal framework and application of emojis in the workplace considering foreign jurisdictions such as the United Kingdom and the United States of America and whether Australia should adopt similar legal approaches to these jurisdictions.

Keywords: emoticons, legal approaches, regulation, workplace

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Authors: K. M. Saif Ur Rahman, Razib Mamun, Himica Arjuman, Fida Al Shams

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Introduction: Autism spectrum disorder (ASD) has become an emerging neurodevelopmental disorder with increasing prevalence. It has become an important public health issue globally. Many approaches including speech and language therapy (SLT), occupational therapy, behavioral therapy etc. are being applied for the betterment of the ASD patients. This study aims to describe the characteristics of ASD patients and perception of caregiver regarding SLT in Bangladesh. Methods: This cross-sectional study was conducted in a therapy and rehabilitation center at Dhaka city. Caregivers of 48 ASD patients responded regarding their perception of SLT and characteristics of patients. Results: Among 48 ASD patients, 56.3% were between 3 to 5 years age group with a male predominance (87.5%). More than half of the participants (56.3%) initiated SLT at the age of 1-3 years and the majority (43.8%) were taking SLT for less than 1 year. Majority of the patients (64.6%) were taken to a physician for healthcare as a first contact of which 29.2% were referred to SLT by physicians. More than half (56.3%) of the caregivers were moderately satisfied with SLT and most of them (62.5%) mentioned moderate improvement through SLT. Improvement rate was 10-15% in specific symptoms such as eye contact, complex mannerism, pointing, imitation etc. Conclusion: This study reveals the self-reported perception of caregivers on SLT. Despite reported improvements, more exploration of different approaches and intervention for management of ASD is recommended.

Keywords: ASD, characteristics, SLT, Bangladesh

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Authors: Nyasha Agnes Gurira, Patrick Ngulube

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Heritage as an asset can be used to achieve cultural and socio-economic development through its careful use as a tourist attraction. Cultural heritage sites, especially those listed as World Heritage sites generate a lot of revenue through their use as tourist attractions. According to article 5(a) of the World Heritage Convention, World Heritage Sites (WHS) must serve a function in the life of the communities. This is further stressed by the International Council on Monuments and Sites (ICOMOS) charter on cultural heritage tourism which recognizes the positive effects of tourism on cultural heritage and underlines that domestic and international tourism is among the foremost vehicles for cultural exchange, conservation should thus provide for responsible and well-managed opportunities for local communities. The inclusion of communities in the world heritage agenda identifies them as the owners of the heritage and partners in the management planning process. This reiterates the need to empower communities and enable them to participate in the decisions which relate to the use of their heritage divorcing from the ideals of viewing communities as beneficiaries from the heritage resource. It recognizes community ownership rights to cultural heritage an element enshrined in Zimbabwe’ national constitution. Through the use of contingency valuation approaches, by assessing the Willingness to pay for visitors at the site the research determined the tourism use value of Great Zimbabwe (WHS). It assessed the extent to which the communities at Great Zimbabwe (WHS) have been developed through the tourism use of the WHS. Findings show that the current management mechanism in place regards communities as stakeholders in the management of the WHS, their ownership and property rights are not fully recognized. They receive indirect benefits from the tourism use of the WHS. This paper calls for a shift in management approach where community ownership rights are fully recognized and more inclusive approaches are adopted to ensure that the goal of sustainable development is achieved. Pro-poor benefits of tourism are key to enhancing the livelihoods of communities and can only be achieved if their rights are recognized and respected.

Keywords: communities, cultural heritage tourism, development, property ownership rights, pro-poor benefits, sustainability, world heritage site

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Authors: Van Thinh Bui, Anh Tuan Tran, Quoc Viet Ngo, The Bao Pham

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Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches.

Keywords: video retrieval, principal objects, keyframe, segmentation of aggregating superpixels, speeded up robust features, bag-of-words, SVM

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Authors: Albina Muratbekova

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One of the main tensions and challenges in the development of Sino-Indian relation is the demarcation of its frontiers. The fact that throughout the history borders had never been demarcated on ground occur a dispute between China and India after receiving sovereignty. Boundaries of India and China are divided into three sectors: Eastern, Middle and Western. The middle sector runs from India’s Uttar Pradesh to the Punjab, 545 km length of the Line of Actual Control, the lines of which was confirmed at the 9th meeting of the Expert Group held in 2001, in New Delhi. Other two sectors are still not determined and cause disputes. A western sector of the frontier is the Aksai Chin plateau, covers areas of Ladakh, Tibet, and Sinkiang. Another disputed area lies in the Eastern sector in the Himalayan region, which after 1986 became the Indian state called Arunachal Pradesh. There are two different approaches in the ways of resolving the border dispute. Chinese side keeps an opinion that the border dispute must be resolved in a timely matter unless it is favorable for China, the resolution can be left to a later generation. While India’s government due to security reasons is eager to demarcate the border. In order to study this conflict was used as a descriptive-comparative-analytical method. Also, it was done a profound analyze of conflict nature.

Keywords: border dispute, China, India, territorial claim

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Authors: Wided Bakari, Patrice Bellot, Omar Trigui, Mahmoud Neji

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This article constitutes an opening to think of the modeling and analysis of Arabic texts in the context of a question-answer system. It is a question of exceeding the traditional approaches focused on morphosyntactic approaches. Furthermore, we present a new approach that analyze a text in order to extract correct answers then transform it to logical predicates. In addition, we would like to represent different levels of information within a text to answer a question and choose an answer among several proposed. To do so, we transform both the question and the text into logical forms. Then, we try to recognize all entailment between them. The results of recognizing the entailment are a set of text sentences that can implicate the user’s question. Our work is now concentrated on an implementation step in order to develop a system of question-answering in Arabic using techniques to recognize textual implications. In this context, the extraction of text features (keywords, named entities, and relationships that link them) is actually considered the first step in our process of text modeling. The second one is the use of techniques of textual implication that relies on the notion of inference and logic representation to extract candidate answers. The last step is the extraction and selection of the desired answer.

Keywords: NLP, Arabic language, question-answering, recognition text entailment, logic forms

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Authors: Jolanta Jonak, Sylvia Tolczyk

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Educational systems are tasked with preparing students for future success in academic or work environments. Schools strive to achieve this goal, but often it is challenging as conventional teaching approaches are often ineffective in increasingly diverse educational systems. In today’s ever-increasing global society, educational systems become increasingly diverse in terms of cultural and linguistic differences, learning preferences and styles, ability and disability. Through increased understanding of disabilities and improved identification processes, students having some form of disabilities tend to be identified earlier than in the past, meaning that more students with identified disabilities are being supported in our classrooms. Also, a large majority of students with disabilities are educated in general education environments. Due to cognitive makeup and life experiences, students have varying learning styles and preferences impacting how they receive and express what they are learning. Many students come from bi or multilingual households and with varying proficiencies in the English language, further impacting their learning. All these factors need to be seriously considered when developing learning opportunities for student's. Educators try to adjust their teaching practices as they discover that conventional methods are often ineffective in reaching each student’s potential. Many teachers do not have the necessary educational background or training to know how to teach students whose learning needs are more unique and may vary from the norm. This is further complicated by the fact that many classrooms lack consistent access to interventionists/coaches that are adequately trained in evidence-based approaches to meet the needs of all students, regardless of what their academic needs may be. One evidence-based way for providing successful education for all students is by incorporating cognitive approaches and strategies that tap into affective, recognition, and strategic networks in the student's brain. This can be done through Differentiated Instruction (DI). Differentiated Instruction is increasingly recognized model that is established on the basic principles of Universal Design for Learning. This form of support ensures that regardless of the students’ learning preferences and cognitive learning profiles, they have opportunities to learn through approaches that are suitable to their needs. This approach improves the educational outcomes of students with special needs and it benefits other students as it accommodates learning styles as well as the scope of unique learning needs that are evident in the typical classroom setting. Differentiated Instruction also is recognized as an evidence-based best practice in education and is highly effective when it is implemented within the tiered system of the Response to Intervention (RTI) model. Recognition of DI becomes more common; however, there is still limited understanding of the effective implementation and use of strategies that can create unique learning environments for each student within the same setting. Through employing knowledge of a variety of instructional strategies, general and special education teachers can facilitate optimal learning for all students, with and without a disability. A desired byproduct of DI is that it can eliminate inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability.

Keywords: differentiated instruction, universal design for learning, special education, diversity

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Authors: Arash Sepehri Bonab

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Techniques to switch cells between development and differentiation, which tend to be commonly exclusive, are utilized in arrange to supply an expansive cell mass that can perform particular separated capacities required for the tissue to develop. Approaches to tissue engineering center on the have to give signals to cell populaces to advance cell multiplication and separation. Current tissue regenerative procedures depend primarily on tissue repair by transplantation of synthetic/natural inserts. In any case, restrictions on the existing procedures have expanded the request for tissue designing approaches. Tissue engineering innovation and stem cell investigation based on tissue building have made awesome advances in overcoming the issues of tissue and organ damage, useful loss, and surgical complications. Bone tissue has the capability to recover itself; in any case, surrenders of a basic estimate anticipate the bone from recovering and require extra support. The advancement of bone tissue building has been utilized to form useful options to recover the bone. This paper primarily portrays current advances in tissue engineering in different fields of bone and talks about the long-term trend of tissue designing innovation in the treatment of complex diseases.

Keywords: tissue engineering, bone, technologies, treatment

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Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: K. D. R. Jagath-Kumara, D. D. Dias

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The sea waves carry thousands of GWs of power globally. Although there are a number of different approaches to harness offshore energy, they are likely to be expensive, practically challenging and vulnerable to storms. Therefore, this paper considers using the near shore waves for generating mechanical and electrical power. It introduces two new approaches, the wave manipulation and using a variable duct turbine, for intercepting very wide wave fronts and coping with the fluctuations of the wave height and the sea level, respectively. The first approach effectively allows capturing much more energy yet with a much narrower turbine rotor. The second approach allows using a rotor with a smaller radius but captures energy of higher wave fronts at higher sea levels yet preventing it from totally submerging. To illustrate the effectiveness of the approach, the paper contains a description and the simulation results of a scale model of a wave manipulator. Then, it includes the results of testing a physical model of the manipulator and a single duct, axial flow turbine, in a wave flume in the laboratory. The paper also includes comparisons of theoretical predictions, simulation results and wave flume tests with respect to the incident energy, loss in wave manipulation, minimal loss, brake torque and the angular velocity.

Keywords: near-shore sea waves, renewable energy, wave energy conversion, wave manipulation

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Siddhartha Chauhan, Nitin Kumar Kotania

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Traditional Wireless Sensor Networks (WSNs) generally use static sinks to collect data from the sensor nodes via multiple forwarding. Therefore, network suffers with some problems like long message relay time, bottle neck problem which reduces the performance of the network. Many approaches have been proposed to prevent this problem with the help of mobile sink to collect the data from the sensor nodes, but these approaches still suffer from the buffer overflow problem due to limited memory size of sensor nodes. This paper proposes an energy efficient scheme for data gathering which overcomes the buffer overflow problem. The proposed scheme creates virtual grid structure of heterogeneous nodes. Scheme has been designed for sensor nodes having variable sensing rate. Every node finds out its buffer overflow time and on the basis of this cluster heads are elected. A controlled traversing approach is used by the proposed scheme in order to transmit data to sink. The effectiveness of the proposed scheme is verified by simulation.

Keywords: buffer overflow problem, mobile sink, virtual grid, wireless sensor networks

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Authors: Johannes Van Der Sandt

Abstract:

This quantitative study investigates different approaches of community singing, in building social capital in South Tyrol, Italy, and South Africa. The impact of the various approaches of community singing is examined by investigating the main components of social capital, namely, social norms and obligations, social networks and associations and trust, and how these components are manifested in two different societies. The research is based on the premise that community singing is an important agent for the development of social capital. It seeks to establish in what form community singing can best enhance the social capital of communities in South Tyrol that are undergoing significant changes in the ways in which social capital is generally being generated on account of demographic, economic, technological and cultural changes. South Tyrol and South Africa share some similarities in the management of their multi-cultural composition. By comparing the different approaches to community singing in two multi-cultural societies, it is hoped to gain insight, and an understanding of the connections between culture, social cohesion, identity and therefore to be able to add to the understanding of the building of social capital through community singing. Participation in music contributes to the growth of social capital in communities, this is amongst others the finding of an ever increasing amount of research. In sociological discourses on social capital generation, the dimension of community music making is recognized as an important factor. Trust and mutual cooperation are products when people listen to each other, when they work or play together, and when they care about each other. This is how social capital develops as an important shared resource. Scholars of Community Music still do not agree on a short and concise definition for Community Music. For the purpose of this research, the author concurs with the definition of Community Music of the Community Music Activity commission of the International Society of Music Education as having the following characteristics: decentralization, accessibility, equal opportunity, and active participation in music-making. These principles are social and political ones, and there can be no doubt that community music activity is more than a purely musical one. Trust, shared norms and values civic and community involvement, networks, knowledge resources, contact with families and friends, and fellowship are key components in fostering group cohesion and social capital development in a community. The research will show that there is no better place for these factors to flourish than in a community singing group. Through this comparative study, it is the aim to identify, analyze and explain similarities and differences in approaches to community across societies that find themselves in a rapid transition from traditional cultural to global cultural habits characterized by a plurality of orientation points, with the aim to gain a better understanding of the various directions South Tyrolean singing culture can take.

Keywords: community music, multicultural, singing, social capital

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Authors: Hari Prasad Nepal

Abstract:

Research on lecture method issues confirm that this teaching method has been practiced from the very beginnings of schooling. Many teachers, lecturers and professors are convinced that lecture still represents main tool of contemporary instructional process. The central purpose of this study is to uncover the extent of using lecture method in the higher education. The study was carried out in Nepalese context with employing mixed method research design. To obtain the primary data this study employed a questionnaire involving items with close and open answers. 120 teachers, lecturers and professors participated in this study. The findings indicated that 75 percent of the respondents use the lecture method in their classroom teaching. The study reveals that there are advantages of using lecture method such as easy to practice, less time to prepare, high pass rate, high students’ satisfaction, little comments on instructors, appropriate to large classes and high level students. In addition, the study divulged the instructors’ reflections and measures to improve the lecture method. This research concludes that the practice of lecture method is still significantly applicable in colleges and universities in Nepalese contexts. So, there are no significant changes in the application of lecture method in the higher education classroom despite the emergence of new learning approaches and strategies.

Keywords: instructors, learning approaches, learning strategies, lecture method

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