Search results for: traditional scheduling algorithms

Authors: Haresh Sharma, Jaimini Luharia

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The ecology in the Western Himalayan region transforms with the change in altitude. This change is observed in terms of topography, species of flora and fauna and the quality of the soil. The current study focuses on women of indigenous communities of Pangi Valley, which is located in the state of Himachal Pradesh, India. The valley is bifurcated into three different areas –Saichu, Hudan Bhatori, and Sural Bhatori valleys. It is one of the most remote, rugged and difficult to access tribal regions of Chamba district. The altitude of the valley ranges from 2,000 m to 6,000 m above sea level. The Pangi valley is inhabited by ‘Pangwals’ and ‘Bhots’ tribes of the Himalayas who speak their local tribal language called’ Pangwali’. The valley is cut-off from the mainland due to heavy snow and lack of proper roads during peak winters. Due to difficult geographical location, the daily lives of the people are constantly challenged, and they are most of the times deprived of benefits targeted through government programs. However, the indigenous communities earn their livelihood through livestock and forest-based produce while some of them migrate to nearby places for better work. The current study involves snowball sampling methodology for data collection along with in-depth interviews of women members of Self-Help Groups and women farmers. The findings reveal that the lives of these indigenous communities largely depend on forest-based products. So, it creates all the more significance of enhancing, maintaining, and consuming natural resources sustainably. Under such circumstances, the women of the community play a significant role of guardians in conservation and protection of the forests. They are the custodians of traditional knowledge of environment conservation practices that have been followed for many years in the region. The present study also sought to establish a relationship between some of the development initiatives undertaken by the women in the valley that stimulate sustainable mountain economy and conservation practices. These initiatives include cultivation of products like hazelnut, ‘Gucchi’ rare quality mushroom, medicinal plants exclusively found in the region, thereby promoting long term sustainable conservation of agro-biodiversity of the Western Himalayan region. The measures taken by the community women are commendable as they ensure access and distribution of natural resources as well as manage them for future generations. Apart from this, the tribal women have actively formed Self-Help Groups promoting financial inclusion through various activities that augment ownership and accountability towards the overall development of the communities. But, the results also suggest that there’s not enough recognition given to women’s role in forests conservation practices due to several local socio-political reasons. There are not enough research studies done on communities of Pangi Valley due to inaccessibility created out of lack of proper roads and other resources. Also, there emerged a need to concretize indigenous and traditional knowledge of conservation practices followed by women in the community.

Keywords: forest conservation, indigenous community women, sustainable livelihoods, sustainable development, poverty alleviation, Western Himalayas

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: Nidhi Gadura

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To ensure student success in a non majors biology course, a flipped classroom pedagogical approach is developed and implemented. All students are assigned online lectures to listen to before they come to class. A three hour lecture is split into one hour of online component, one hour of in class lecture and one hour of worksheets done by students in the classroom. This deviation from a traditional 3 hour in class lecture has resulted in increased student interest in science as well as better understanding of difficult scientific concepts. A pre and post survey was given to measure the interest rates and grades were used to measure the success rates. While the overall grade average did not change dramatically, students reported a better appreciation of biology. Also, students overwhelmingly like the use of worksheets in class to help them understand the concepts. They liked the fact that they could listen to lectures at their own pace on line and even repeat if needed. The flipped classroom approach turned out to work really well our non science majors and the author is ready to implement this in other classrooms.

Keywords: flipped classroom, non science majors, pedagogy, technological pedagogical model

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Authors: Vijaya K. Narne, Gerard Loquet, Tobias Piechowiak, Dorte Hammershoi, Jesper H. Schmidt

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BEAR, which stands for better hearing rehabilitation is a large-scale project in Denmark designed and executed by three national universities, three hospitals, and the hearing aid industry with the aim to improve hearing aid fitting. A total of 1963 hearing impaired people were included and were segmented into subgroups based on hearing-loss, demographics, audiological and questionnaires data (i.e., the speech, spatial and qualities of hearing scale [SSQ-12] and the International Outcome Inventory for Hearing-Aids [IOI-HA]). With the aim to provide a better hearing-aid fit to individual patients, we applied modern machine learning techniques with traditional audiograms rule-based systems. Results show that age, speech discrimination scores, and audiogram configurations were evolved as important parameters in characterizing sub-population from the data-set. The attempt to characterize sub-population reveal a clearer picture about the individual hearing difficulties encountered and the benefits derived from more individualized hearing aids.

Keywords: hearing loss, audiological data, machine learning, hearing aids

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Authors: Kars Beek, Remco Groeneveld, Sjaak Brinkkemper

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Although there is much literature available on requirement documentation in traditional software development, few studies have been conducted about this topic in open source software development. While open-source software development is becoming more important, the software development processes are often not as structured as corporate software development processes. Papers show that communities, creating open-source software, often lack structure and documentation. However, most recent studies about this topic are often ten or more years old. Therefore, this research has been conducted to determine if the lack of structure and documentation in requirement engineering is currently still the situation in these communities. Three open-source products have been chosen as subjects for conducting this research. The data for this research was gathered based on interviews, observations, and analyses of feature proposals and issue tracking tools. In this paper, we present a comparison and an analysis of the different methods used for requirements documentation to understand the current practices of requirements documentation in open source software development.

Keywords: case study, open source software, open source software development, requirement elicitation, requirement engineering

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Srie Rezeki Nur Endah, Richa Mardianingrum

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Cancer is one of the most feared diseases and is considered the leading cause of death worldwide. Generally, cancer drugs are synthetic drugs with relatively more expensive prices and have harmful side effects, so many people turn to traditional medicine, for example by utilizing herbal medicine. Erythrina poeppigiana is one of the plants that can be used as a medicinal plant containing 10,11-dihidroerisodin compounds that are useful anticancer etnofarmakologi. The purpose of this study was to identify the target of 10,11 dihydroerisodin receptor compound as in silico anticancer candidate. The pure isolate was tested physicochemically by MS (Mass Spectrometry), UV-Vis (Ultraviolet – Visible), IR (Infra Red), 13C-NMR (Carbon-13 Nuclear Magnetic Resonance), 1H-NMR (Hydrogen-1 Nuclear Magnetic Resonance), to obtain the structure of 10,11-dihydroerisodin alkaloid compound then identified to target receptors in silico. From the results of the study, it was found that 10,11-dihydroerisodin compound can work on the Serine / threonine-protein kinase Chk1 receptor that serves as an anti-cancer candidate.

Keywords: anti-cancer, Erythrina poeppigiana, target receptor, 10, 11- dihidroerisodin

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Authors: Penn P. Wu

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Recent advances in virtual reality (VR) technologies have made it possible for students to experience a virtual on-the-scene or virtual in-person observation of an educational event. In an experimental class, the author uses VR, particularly 360° videos, to virtually engage students in an event, through a wide spectrum of educational resources, such s a virtual “bystander.” Students were able to observe the event as if they were physically on site, although they could not intervene with the scene. The author will describe the adopted equipment, specification, and cost of building them as well as the quality of VR. The author will discuss (a) feasibility, effectiveness, and efficiency of using VR as a supplemental technology to teach college students and criteria and methodologies used by the authors to evaluate them; (b) barriers and issues of technological implementation; and (c) pedagogical practices learned through this experiment. The author also attempts to explore (a) how VR could provide an interactive virtual in-person learning experience; (b) how VR can possibly change traditional college education and online education; (c) how educators and balance six critical factors: cost, time, technology, quality, result, and content.

Keywords: learning with VR, virtual experience of learning, virtual in-person learning, virtual reality for education

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Authors: Chamin Chimyang

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The fast-changing global trend and declining forest region have impacted agricultural lands; animals, especially birds, might become one of the major pests in the near future and go neglected or unreported in many kinds of literature and events, which is mainly because of bird infestation being a pocket-zone problem. This bird infestation can be attributed to the balding of the forest region and the decline in their foraging hotspot due to anthropogenic activity. There are many ways to keep away the birds from agricultural fields, both conventional and non-conventional. But the question here is whether the traditional approach of bird scarring methods such as scare-crows are effective enough. There are many traits in rice that are supposed to keep the birds away from foraging in paddy fields, and the selection of such traits might be rewarding, such as the angle of the flag leaf from the stem, grain size, novelty of any trait in that particular region and also an awning. Awning, as such, is a very particular trait on which negative selection was imposed to such an extent that there has been a decline in the nucleotide responsible for the said trait. Thus, in this particular session, histology, genetics, genes behind the trait and how awns might be one of the solutions to the problem stated above will be discussed in detail.

Keywords: bird infestation, awning, negative selection, domestication

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Authors: Andrés Lara Guillén, José M. Soriano Disla, Gemma Castejón Martínez, David Fernández-Gutiérrez

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The worldwide population is exponentially increasing, which causes a rising demand for food, energy and non-renewable resources. These demands must be attended to from a circular economy point of view. Under this approach, the obtention of strategic products from biowaste is crucial for the society to keep the current lifestyle reducing the environmental and social issues linked to the lineal economy. This is the main objective of the VALUEWASTE project. VALUEWASTE is about valorizing urban biowaste into proteins for food and feed and biofertilizers, closing the loop of this waste stream. In order to achieve this objective, the project validates three value chains, which begin with the anaerobic digestion of the biowaste. From the anaerobic digestion, three by-products are obtained: i) methane that is used by microorganisms, which will be transformed into microbial proteins; ii) digestate that is used by black soldier fly, producing insect proteins; and iii) a nutrient-rich effluent, which will be transformed into biofertilizers. VALUEWASTE is an innovative solution, which combines different technologies to valorize entirely the biowaste. However, it is also required to demonstrate that the solution is greener than other traditional technologies (baseline systems). On one hand, the proteins from microorganisms and insects will be compared with other reference protein production systems (gluten, whey and soybean). On the other hand, the biofertilizers will be compared to the production of mineral fertilizers (ammonium sulphate and synthetic struvite). Therefore, the aim of this study is to provide that biowaste valorization can reduce the environmental impacts linked to both traditional proteins manufacturing processes and mineral fertilizers, not only at a pilot-scale but also at an industrial one. In the present study, both baseline system and VALUEWASTE solution are evaluated through the Environmental Life Cycle Assessment (E-LCA). The E-LCA is based on the standards ISO 14040 and 14044. The Environmental Footprint methodology was the one used in this study to evaluate the environmental impacts. The results for the baseline cases show that the food proteins coming from whey have the highest environmental impact on ecosystems compared to the other proteins sources: 7.5 and 15.9 folds higher than soybean and gluten, respectively. Comparing feed soybean and gluten, soybean has an environmental impact on human health 195.1 folds higher. In the case of biofertilizers, synthetic struvite has higher impacts than ammonium sulfate: 15.3 (ecosystems) and 11.8 (human health) fold, respectively. The results shown in the present study will be used as a reference to demonstrate the better environmental performance of the bio-based products obtained through the VALUEWASTE solution. Other originalities that the E-LCA performed in the VALUEWASTE project provides are the diverse direct implications on investment and policies. On one hand, better environmental performance will serve to remove the barriers linked to these kinds of technologies, boosting the investment that is backed by the E-LCA. On the other hand, it will be a germ to design new policies fostering these types of solutions to achieve two of the key targets of the European Community: being self-sustainable and carbon neutral.

Keywords: anaerobic digestion, biofertilizers, circular economy, nutrients recovery

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Authors: Ramesh Rajagopalan, Adam Dahlstrom

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Noise removal techniques play a vital role in the performance of electrocardiographic (ECG) signal processing systems. ECG signals can be corrupted by various kinds of noise such as baseline wander noise, electromyographic interference, and power-line interference. One of the significant challenges in ECG signal processing is the degradation caused by additive 50 or 60 Hz power-line interference. This work investigates the removal of power line interference and suppression of transient response for filtering noise corrupted ECG signals. We demonstrate the effectiveness of Infinite Impulse Response (IIR) notch filter with time varying pole radius for improving the transient behavior. The temporary change in the pole radius of the filter diminishes the transient behavior. Simulation results show that the proposed IIR filter with time varying pole radius outperforms traditional IIR notch filters in terms of mean square error and transient suppression.

Keywords: notch filter, ECG, transient, pole radius

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Authors: Sonia Wahengbam, Natasha Elangbam

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Female impersonation has existed through the length of human civilization and the breadth of its cultures. Transvestism and drag queen cultures have created multi-sited spaces where in the shadow of art, one can cross the gender barrier and express one’s hidden identity. This paper will explore a dynamic cultural space that exists in Manipur, a state in the northeastern region of India, where the female impersonators (nupi shabis) of a folk theater (Shumang Leela) are using this traditional and popular art form to claim social acceptance of their homosexual identities through the medium of entertainment. It will highlight how by crossing the gender boundary, this third gender group has carved out a unique socio-economic niche where they have exploited their sexual identities to their advantage. The paper will trace the expanding cultural ‘’borderland’’ of Manipur where there is an increasing sense of ‘becoming’, belonging and sharing” of identities through the interweaving of old and new media. The research will be based on interviews with the nupi shabis, cultural critics and other experts.

Keywords: transvestism, Manipur, female impersonators (nupi shabis), Shumang Leela, gender

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Judith Sue Hwa Joo

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Guanyin (Avalokiteśvara in Sanskrit), the Bodhisattva of Mercy and Compassion, is the most widely worshipped Buddhist Divinity in Chinese societies and is also believed by more than half of Asian populations across various countries. The most overwhelming reason for the popularity of Guanyin in Chinese societies is, according to the Lotus Sutra, that Guanyin would apperceive voices of those suffering from immense afflictions and troubles, and liberate them upon crying for his/her holy name with wholeheartedness. Its pervasive social influence has spanned more than two thousand years and is still deeply affecting the lives of most Chinese people. This study aimed to investigate whether Guanyin Worship has evolved and changed in modern Chinese societies across the Taiwan Strait. Taiwan and China, albeit having the same language and culture, have been territorially divided and governed by two different political regimes for over 70 years. It would be scientifically intriguing to unveil any substantial changes in religious behaviors in the context of Guanyin Worship. A comprehensive anonymous questionnaire survey in Chinese communities was conducted from October 2017 to May 2019 across various countries, mostly in China, Taiwan, and Hong Kong areas. Since the religious survey is officially prohibited in China, the study was difficult and could only be exercised by means of snowball sampling. Demographic data (age, sex, education, religious belief) were registered and Guanyin’s salvation functions under various confronting situations were investigated. Psychological dimensions of religious belief in Guanyin were probed in terms of the worship experience, the willingness of veneration, and egoistic or altruistic ideations. A literature review on documented functional attributes was carried out in parallel for comparison analyses with traditional roles. Effective 1123 out of 1139 samples were obtained. Statistical analysis revealed that Guanyin Worship is still commonly practiced and deeply rooted in the hearts of all Chinese people regardless of gender, age, education, and residential area, even though they may not enshrine Guanyin at home nowadays. The conventional roles of Guanyin Bodhisattva are still valid and best satisfy the real interests of lifestyles in modern times. When comparing the traditional Buddhist Sutra and the documented literature, the divine power of modern Guanyin has notably empowered to recover, protect and transform fetal and infant spirits due to the sexual liberation, increased abortion rate, gender awakening and enhanced female autonomy in the reproductive decision. However, the One-Child policy may have critically impacted the trajectory of Guanyin Worship so that people in China prevail over those in Taiwan praying for aborted lives or premature deaths. Furthermore, particularly in Hong Kong and Macao, Guanyin not only serves as the sea guardian for the fishermen but also additional services a new function as the God of Wealth. The divine powers and salvation functions of Guanyin are indeed evolving and expanding to comply with the modern psychosocial, cultural and societal needs. This study sheds light on the modernization process of the two-thousand-year-old Guanyin Worship of contemporary Chinese societies.

Keywords: Buddhism, Guanyin, religious behavior, salvation function

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Authors: Wei Zhang

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With the rapid development of deep learning, neural network and deep learning algorithms play a significant role in various practical applications. Due to the high accuracy and good performance, Convolutional Neural Networks (CNNs) especially have become a research hot spot in the past few years. However, the size of the networks becomes increasingly large scale due to the demands of the practical applications, which poses a significant challenge to construct a high-performance implementation of deep learning neural networks. Meanwhile, many of these application scenarios also have strict requirements on the performance and low-power consumption of hardware devices. Therefore, it is particularly critical to choose a moderate computing platform for hardware acceleration of CNNs. This article aimed to survey the recent advance in Field Programmable Gate Array (FPGA)-based acceleration of CNNs. Various designs and implementations of the accelerator based on FPGA under different devices and network models are overviewed, and the versions of Graphic Processing Units (GPUs), Application Specific Integrated Circuits (ASICs) and Digital Signal Processors (DSPs) are compared to present our own critical analysis and comments. Finally, we give a discussion on different perspectives of these acceleration and optimization methods on FPGA platforms to further explore the opportunities and challenges for future research. More helpfully, we give a prospect for future development of the FPGA-based accelerator.

Keywords: deep learning, field programmable gate array, FPGA, hardware accelerator, convolutional neural networks, CNN

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Authors: Ani Kojoyan

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Linguistic studies have been investigating a connection between gender and linguistic development since 1970s. Scholars claim that gender differences in first and second language learning are socially constructed. Recent studies to language learning and gender reveal that second language acquisition is also a social phenomenon directly influencing one’s gender identity. Those responsible for designing language learning-teaching materials should be encouraged to understand the importance of and address the gender sensitivity accurately in textbooks. Writing or compiling a textbook is not an easy task; it requires strong academic abilities, patience, and experience. For a long period of time Armenia has been involved in the compilation process of a number of foreign language textbooks. However, there have been very few discussions or evaluations of those textbooks which will allow specialists to theorize that practice. The present paper focuses on the analysis of gender sensitivity issues and policy aspects involved in an EFL textbook. For the research the following material has been considered – “A Basic English Grammar: Morphology”, first printed in 2011. The selection of the material is not accidental. First, the mentioned textbook has been widely used in university teaching over years. Secondly, in Armenia “A Basic English Grammar: Morphology” has considered one of the most successful English grammar textbooks in a university teaching environment and served a source-book for other authors to compile and design their textbooks. The present paper aims to find out whether an EFL textbook is gendered in the Armenian teaching environment, and whether the textbook compilers are aware of gendered messages while compiling educational materials. It also aims at investigating students’ attitude toward the gendered messages in those materials. And finally, it also aims at increasing the gender sensitivity among book compilers and educators in various educational settings. For this study qualitative and quantitative research methods of analyses have been applied, the quantitative – in terms of carrying out surveys among students (45 university students, 18-25 age group), and the qualitative one – by discourse analysis of the material and conducting in-depth and semi-structured interviews with the Armenian compilers of the textbook (interviews with 3 authors). The study is based on passive and active observations and teaching experience done in a university classroom environment in 2014-2015, 2015-2016. The findings suggest that the discussed and analyzed teaching materials (145 extracts and examples) include traditional examples of intensive use of language and role-modelling, particularly, men are mostly portrayed as active, progressive, aggressive, whereas women are often depicted as passive and weak. These modeled often serve as a ‘reliable basis’ for reinforcing the traditional roles that have been projected on female and male students. The survey results also show that such materials contribute directly to shaping learners’ social attitudes and expectations around issues of gender. The applied techniques and discussed issues can be generalized and applied to other foreign language textbook compilation processes, since those principles, regardless of a language, are mostly the same.

Keywords: EFL textbooks, gender policy, gender sensitivity, qualitative and quantitative research methods

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Authors: Shraddha Mahore Manjrekar

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Culture has been an integral part of the civilizations in the world. Architectural works, in the material form of buildings, are often perceived as cultural symbols and as works of art. Historical civilizations are often identified with their surviving architectural achievements. Author has observed and thought about the relation of Indian traditional cultural beliefs and their relation to the sustainable environment. There are some unwritten norms regarding the use of resources and the environment in Indian continent, that have been commonly accepted by the people for building houses and settlements since the Vedic period . The research has been done on the chanting and prayers done in a number of houses and temples in Madhya Pradesh and Maharashtra. After doing some research, it was also found that resource assessment had also been done for the entire country, and an idea of conservation of these resources was imbibed in the common people by means of some traditions, customs and beliefs. The sensitization and gratefulness about natural resources have been observed in the major beliefs and customs. This paper describes few of such beliefs and customs that are directly linked with the built environment and landscape.

Keywords: Indian culture, sacred groves, sustainability in built environment, sustainability practices

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Authors: Kübra Aktaş, Nihat Akin

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Tarhana is a traditional Turkish fermented food. It is widely consumed as soup and includes many different ingredients such as wheat flour, various vegetables, and spices, yoghurt, bakery yeast. It can also be enriched by adding other ingredients. Thus, its nutritional properties can be enhanced. In this study, tarhana was supplemented with two different types of brans (rice bran and corn bran) and WPC (whey protein concentrate powder) to improve its nutritional and functional properties. Some chemical properties of tarhana containing two different brans and their levels (0, 5, 10 and 15%) and WPC (0, 5, 10%) were investigated. The results indicated that addition of WPC increased ash content in tarhanas which were fortified with rice and corn bran. The highest antioxidant and phenolic content values were obtained with addition of rice bran in tarhana formulation. Compared to tarhana with corn bran, rice bran addition gave higher oil content values. The cellulose content of tarhana samples was determined between 0.75% and 2.74% and corn bran showed an improving effect on cellulose contents of samples. In terms of protein content, addition of WPC into the tarhana raised protein content for the samples.

Keywords: corn, rice, tarhana, whey

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Xiaohan Bookman, Xiaoyan Zhu

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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

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Authors: Aneri Mehta, Krunal Mehta

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Administration is largely based on two sciences: ‘management science’ and ‘political science’. The approach of new public management is more inclined towards the management science. Era of ‘New Public Management’ has affected the developing countries very immensely. Public management reforms are needed to enhance the development of the countries. This reform mainly includes capacity building, control of corruption, political decentralization, debureaucratization and public empowerment. This gives the opportunity to create self-sustaining change in the governance. This paper includes the link of approach of new public management and their effect on building effective democratization in the country. This approach mainly focuses on rationality and effectiveness of governance system. These need to have deep efforts on technological, organizational, social and cultural fields. Bringing citizen participation in governance is main objective of NPM. The shift from traditional public management to new public management have low success rate of reforms. This research includes case study of RTI which is a big step of government towards citizen centric approach of governance. The aspect of ‘publicness’ in the democratic policy implementation is important for good governance in India.

Keywords: public management, development, public empowerment, governance

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Authors: Wahid Ahmad Dar, Irshad Ahmad Najar

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The influence of social media is percolating to every corner of our social life. It is also changing the social sphere of the classroom in particular and education in general. This paper tries to explore the ways in which social media is influencing student-teacher relationship. Differences have been found in student’s ability to draw benefits from using ICT. Besides digital divides in access and usage, there are attitudinal differences among students towards ICT aligned with traditional forms of social differences. The paper particularly focusses on how students from diverse backgrounds are using social media to interact with their teachers and how such interactions differ on the basis of social class, gender and residential background of students. A qualitative research methodology has been used for answering these questions. Open-ended questionnaire has been designed and administered to a sample of postgraduate students from University of Kashmir drawn purposively ensuring optimum number of subjects from all backgrounds. The data were analyzed by content analysis, deciphering general patterns in the data.

Keywords: social media, student-teacher relationship, social class, gender

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Authors: Usman Jilani, Ibad Khurram, Irshad Hussain

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Environmentally sustainable waste management is a challenging task as it involves multiple and diverse economic, environmental, technical and regulatory issues. Municipal Solid Waste Management (MSWM) is more challenging in developing countries like Pakistan due to lack of awareness, technology and human resources, insufficient funding, inefficient collection and transport mechanism resulting in the lack of a comprehensive waste management system. This work presents an overview of current MSWM practices in Peshawar, the provincial capital of Khyber Pakhtunkhwa, Pakistan and proposes a better and sustainable integrated solid waste management system with incineration (Waste to Energy) option. The diverted waste would otherwise generate revenue; minimize land fill requirement and negative impact on the environment. The proposed optimized solution utilizing scientific techniques (like mathematical modeling, optimization algorithms and GIS) as decision support tools enhances the technical & institutional efficiency leading towards a more sustainable waste management system through incorporating: - Improved collection mechanisms through optimized transportation / routing and, - Resource recovery through incineration and selection of most feasible sites for transfer stations, landfills and incineration plant. These proposed methods shift the linear waste management system towards a cyclic system and can also be used as a decision support tool by the WSSP (Water and Sanitation Services Peshawar), agency responsible for the MSWM in Peshawar.

Keywords: municipal solid waste management, incineration, mathematical modeling, optimization, GIS, Peshawar

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Authors: Borys Stegniy, Anton Gerilovych, Oleksii Solodiankin, Vitaliy Bolotin, Anton Stegniy, Denys Muzyka, Claudio Afonso

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New APMV was isolated from white fronted goose in Ukraine. This isolate was tested serologically using monoclonal antibodies in haemagglutination-inhibition tests against APMV1-9. As the results obtained isolate showed cross reactions with APMV7. Following investigations were provided for the full genome sequencing using random primers and cloning into pCRII-TOPO. Analysis of 100 transformed colonies of E.coli using traditional sequencing gave us possibilities to find only 3 regions, which could identify by BLAST. The first region with the length of 367 bp had 70 % nucleotide sequence identity to the APMV 12 isolate Wigeon/Italy/3920_1/2005 at genome position 2419-2784. Next region (344 bp) had 66 % identity to the same APMV 12 isolate at position 4760-5103. The last region (365 bp) showed 71 % identity to Newcastle disease virus strain M4 at position 12569-12928.

Keywords: APMV, Newcastle disease virus, Ukraine, full genome sequencing

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Authors: Sami Michael Ayodele

Abstract:

Cordyceps are members of the fungi family Cordycepitaceae which are formally in Clavicipitaceae. They parasitize the larvae and adults of different susceptible arthropods. They are highly priced and have been reported to be highly medicinal. Cordyceps have been used for centuries in traditional medicine in China and other Asian countries. Survey studies were carried out to determine the presence of Cordyceps and another entomopathogenic fungal floral in North Central Nigeria for two consecutive years. Thirty samples were collected, twenty-eight were identified, and two were unidentified. Most identified species belong to Ophiocordyceps species (20samples), Cordyceps species (4samples) and Isaria species (4samples). The species identified were: Cordyceps pseudomilitaris, Cordyceps tuberculata, Cordyceps cylindrical, Ophiocordyceps nutans, O. criminals, O. oxycephala, O. kniphofioides and Isaria sinclairii. The morphological and microscopic features of the collected and identified species were similar to those reported in other countries. This is the first official report on the presence of Cordyceps species in Nigeria. Further collections from different ecological regions of Nigeria will show the richness of the floral diversity of these entomopathogenic and medicinal mushrooms in Nigeria.

Keywords: cordyceps, entomopathogenic, medicinal, North Central, Nigeria

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Authors: R. Odoh, M. S. Dauda, E. A. Kamba, N. C. Igwemmar

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Honey and honey trade is an important economic activity for many tropical rural and urban areas worldwide. In West Africa and other part of the world, honey and honey products holds high socio–cultural, religious, medicinal and traditional values. Therefore, to maximize benefits or to enhance profit, a variety of components are added to the raw, fresh and unprocessed honey, introducing the possibility of heavy metals contaminants. Therefore the honey sold in various places, markets and shops in some states in Northern Nigeria (Benue, Nassarawa and Taraba) including Abuja FCT, in Nigeria was analyzed to determine the level of heavy metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn). All the honey samples contain heavy metals. The results ranged from 0.028–0.070, 0.023–0.058, 0.042–0.092, 4.231–8.589, 8.115–14.892, 0.078–0.922, 0.044–0.092, 0.041–0.087 and 18.234–28.654 μg/L for Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn respectively. The mean concentration (μg/L) of the heavy metals Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn of the regularly marketed honey is significantly higher than the mean concentration observed in raw, fresh and unprocessed honey. However, continued consumption of honey with high heavy metal content might lead to exposure to chronic heavy metal poisoning.

Keywords: honey, health, mineral profile adulteration, contamination

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Authors: Andreia Cortes, Carla Pimentel-Rodrigues, Joao Almeida, Myriam Kanoun-Boule, Carla Carvalho, Antonio Tadeu, Armando Silva-Afonso

Abstract:

The adoption of green infrastructure is nowadays encouraged as an essential measure of urban planning and territorial development whenever it offers a better alternative, or is complementary, to current solutions. Green walls and living facades often provide healthy alternatives to traditional grey infrastructures, offering many benefits for both citizens and cities. Beyond the ability to improve environmental conditions and quality of life, they can augment the energy efficiency of buildings, enhance biodiversity and deliver a range of ecosystem services such as water purification, reduction of the urban heat island effect, improvement of air quality and climate change adaptation. For this communication, a systematic survey of the existing green walls and living facades in Portugal was carried out. Different systems were analyzed and compared in terms of dimensions, constructive solutions, vegetative species, maintenance necessities and environmental aspects.

Keywords: green buildings, green walls, living facades, sustainability construction

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Authors: Derejaw Lake Melie, Alemu Kumlachew Tegegne

Abstract:

The increasing prevalence of social media in Ethiopia has exacerbated societal challenges by fostering the proliferation of negative emotional posts and comments. Illicit use of social media has further exacerbated divisions among the population. Addressing these issues through manual identification and aggregation of emotions from millions of users for swift decision-making poses significant challenges, particularly given the rapid growth of Amharic language usage on social platforms. Consequently, there is a critical need to develop an intelligent system capable of automatically detecting and categorizing negative emotional content into social, religious, and political categories while also filtering out toxic online content. This paper aims to leverage sentiment analysis techniques to achieve automatic detection and filtering of negative emotional content from Amharic social media texts, employing a comparative study of deep learning algorithms. The study utilized a dataset comprising 29,962 comments collected from social media platforms using comment exporter software. Data pre-processing techniques were applied to enhance data quality, followed by the implementation of deep learning methods for training, testing, and evaluation. The results showed that CNN, GRU, LSTM, and Bi-LSTM classification models achieved accuracies of 83%, 50%, 84%, and 86%, respectively. Among these models, Bi-LSTM demonstrated the highest accuracy of 86% in the experiment.

Keywords: negative emotion, emotion detection, social media filtering sentiment analysis, deep learning.

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Authors: Ercan Eker, Muhammer Karaman, Akif Aslan, Hakan Tanrikuluoglu

Abstract:

Deficiency of institutional memory and knowledge management can result in information security breaches, loss of prestige and trustworthiness and the worst the loss of know-how and institutional knowledge. Traditional learning management within organizations is generally handled by personal efforts. That kind of struggle mostly depends on personal desire, motivation and institutional belonging. Even if an organization has highly motivated employees at a certain time, the institutional knowledge and memory life cycle will generally remain limited to these employees’ spending time in this organization. Having a learning management system in an organization can sustain the institutional memory, knowledge and know-how in the organization. Learning management systems are much more needed especially in public organizations where the job rotation is frequently seen and managers are appointed periodically. However, a learning management system should not be seen as an organizations’ website. It is a more comprehensive, interactive and user-friendly knowledge management tool for organizations. In this study, the importance of using learning management systems in the process of emerging tacit knowledge is underlined.

Keywords: knowledge management, learning management systems, tacit knowledge, institutional memory

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Authors: Grant Bifolchi

Abstract:

As global environmental problems continue to have highly adverse effects, finding long-term, sustainable solutions to combat ecological distress are of growing paramount concern. Ghost Gear—also known as abandoned, lost or otherwise discarded fishing gear (ALDFG) and derelict fishing gear (DFG)—represents one of the greatest threats to the world’s oceans, posing a significant hazard to human health, livelihoods, and global food security. In fact, according to the UN Food and Agriculture Organization (FAO), abandoned, lost and discarded fishing gear represents approximately 10% of marine debris by volume. Around the world, many governments, governmental and non-profit organizations are doing their best to manage the reporting and retrieval of nets, lines, ropes, traps, floats and more from their respective bodies of water. However, these organizations’ ability to effectively manage files and documents about the environmental problem further complicates matters. In Ghost Gear monitoring and management, organizations face additional complexities. Whether it’s data ingest, industry regulations and standards, garnering actionable insights into the location, security, and management of data, or the application of enforcement due to disparate data—all of these factors are placing massive strains on organizations struggling to save the planet from the dangers of Ghost Gear. In this 90-minute educational session, globally recognized Ghost Gear technology expert Grant Bifolchi CET, BBA, Bcom, will provide real-world insight into how governments currently manage Ghost Gear and the technology that can accelerate success in combatting ALDFG and DFG. In this session, attendees will learn how to: • Identify specific technologies to solve the ingest and management of Ghost Gear data categories, including type, geo-location, size, ownership, regional assignment, collection and disposal. • Provide enhanced access to authorities, fisheries, independent fishing vessels, individuals, etc., while securely controlling confidential and privileged data to globally recognized standards. • Create and maintain processing accuracy to effectively track ALDFG/DFG reporting progress—including acknowledging receipt of the report and sharing it with all pertinent stakeholders to ensure approvals are secured. • Enable and utilize Business Intelligence (BI) and Analytics to store and analyze data to optimize organizational performance, maintain anytime-visibility of report status, user accountability, scheduling, management, and foster governmental transparency. • Maintain Compliance Reporting through highly defined, detailed and automated reports—enabling all stakeholders to share critical insights with internal colleagues, regulatory agencies, and national and international partners.

Keywords: ghost gear, ALDFG, DFG, abandoned, lost or otherwise discarded fishing gear, data, technology

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