Cyber bullying identification and tackling using natural language processing techniques

Abstract. As offensive content has a detrimental influence on the internet and especially in social media, there has been much research identifying cyberbullying posts from social media datasets. Previous works on this topic have overlooked the problems for cyberbullying categories detection, impact of feature choice, negation handling, and dataset construction. Indeed, many natural language processing (NLP) tasks, including cyberbullying detection in texts, lack comprehensive manually labeled datasets limiting the application of powerful supervised machine learning algorithms, including neural networks. Equally, it is challenging to collect large scale data for a particular NLP project due to the inherent subjectivity of labeling task and man-made effort. For this purpose, this thesis attempts to contribute to these challenges by the following. We first collected and annotated a multi-category cyberbullying (10K) dataset from the social network platform (ask.fm). Besides, we have used another publicly available cyberbullying labeled dataset, ’Formspring’, for comparison purpose and ground truth establishment. We have devised a machine learning-based methodology that uses five distinct feature engineering and six different classifiers. The results showed that CNN classifier with Word-embedding features yielded a maximum performance amidst all state-of-art classifiers, with a detection accuracy of 93\% for AskFm and 92\% for FormSpring dataset. We have performed cyberbullying category detection, and CNN architecture still provide the best performance with 81\% accuracy and 78\% F1-score on average. Our second purpose was to handle the problem of lack of relevant cyberbullying instances in the training dataset through data augmentation. For this end, we developed an approach that makes use of wordsense disambiguation with WordNet-aided semantic expansion. The disambiguation and semantic expansion were intended to overcome several limitations of the social media (SM) posts/comments, such as unstructured content, limited semantic content, among others, while capturing equivalent instances induced by the wordsense disambiguation-based approach. We run several experiments and disambiguation/semantic expansion to estimate the impact of the classification performance using both original and the augmented datasets. Finally, we have compared the accuracy score for cyberbullying detection with some widely used classifiers before and after the development of datasets. The outcome supports the advantage of the data-augmentation strategy, which yielded 99\% of classifier accuracy, a 5\% improvement from the base score of 93\%. Our third goal related to negation handling was motivated by the intuitive impact of negation on cyberbullying statements and detection. Our proposed approach advocates a classification like technique by using NegEx and POS tagging that makes the use of a particular data design procedure for negation detection. Performances using the negation-handling approach and without negation handling are compared and discussed. The result showed a 95\% of accuracy for the negated handed dataset, which corresponds to an overall accuracy improvement of 2\% from the base score of 93\%. Our final goal was to develop a software tool using our machine learning models that will help to test our experiments and provide a real-life example of use case for both end-users and research communities. To achieve this objective, a python based web-application was developed and successfully tested

Surface Runoff Responses to Suburban Growth: An Integration of Remote Sensing, GIS, and Curve Number

Suburban growth and its impacts on surface runoff were investigated using the soil conservation service curve number (SCS-CN) model, compared with the integrated advanced remote sensing and geographic information system (GIS)-based integrated approach, over South Kingston, Rhode Island, USA. This study analyzed and employed the supervised classification method on four Landsat images from 1994, 2004, 2014, and 2020 to detect land-use pattern changes through remote sensing applications. Results showed that 68.6% urban land expansion was reported from 1994 to 2020 in this suburban area. After land-use change detection, a GIS-based SCS-CN model was developed to examine suburban growth and surface runoff estimation. The developed model demonstrated the spatial distribution of runoff for each of the studied years. The results showed an increasing spatial pattern of 2% to 10% of runoff from 1994 to 2020. The correlation between runoff co-efficient and rainfall indicated the significant impact of suburban growth in surface runoff over the last 36 years in South Kingstown, RI, USA, showing a slight change of forest (8.2% area of the total area) and agricultural land (4.8% area of the total area). Suburban growth began after 2000, and within 16 years this land-use change started to show its substantial impact on surface runoff. We concluded that the proposed integrated approach could classify land-use and land cover information to understand suburban growth and its potential impact on the area

On mitigating hop-to-hop congestion problem in IoT enabled Intra-Vehicular communication

Internet of Things enabled Intra-Vehicular Network (IVN) refers to the network where large number of sensors are connected with each other for sharing the vehicle's status information in order to develop a smart vehicular system. The number of sensor nodes in the vehicle has increased significantly due to the increasing vehicular applications. The phenomenon of congestion poses a problem in the IVN where the traffic load and number of sensors are increased. This problem can be resolved by mitigating the limitation of the existing Media Access Control (MAC) protocols. In this paper, we address this issue and proposed a MAC strategy for solving this problem in this network. Furthermore, we discuss the design of IVN scenario and the performance is evaluated in terms of end-to-end delay. The simulation results reveal the effectiveness of our proposal

Bio-Rational Management of Maize Weevil, Sitophilus Zeamais in Maize (Zea Mays) Seeds

Bangladesh is a sub-tropical and humid country. That is why, the infestation of insects during storage is very common here. The maize weevil, Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae), locally known as “Katta Poka”, is one of the most serious cosmopolitan pest of stored cereal grain, especially of maize (Zea mays L.), in tropical and subtropical regions including Bangladesh. Considering the issue, the study was conducted in the laboratory of Department of Entomology, Bangladesh Agricultural University (BAU) following completely randomized design (CRD) with three replications to evaluate the efficacy of four locally available botanicals and chemicals. The botanicals used were: Neem (Azadirachta indica) leaf, Datura (Datura stramonium) leaf, Nishinda (Vitex negundo L) leaf and Garlic (Allium sativum L.) tablet powders at three different doses (3, 4 and 5gm)/100g of grain seed against maize weevil. The results revealed that all test materials at 5g doses exhibited higher mortality action against maize weevil while at 3g doses it gave the lowest percentage efficacy. Powdered leaves of neem and datura at 4 and 5gm were showed statistical significant (P<0.01) differences while powdered leaves of nishinda at the similar rates were observed with moderately effectiveness and powdered tablet of garlic gave the lowest mortality rate within 28 days of exposure in all tested doses. These findings suggest that botanical treatments exerted better mortality of maize weevil and reduced maize seed weight loss with higher germination capacity compared to the untreated control. It was also observed that the highest mortality percentage, lowest seed weight loss and highest germination capacity in the seeds which were treated with Sevin 85SP at the rate of 0.25g/100g maize seeds. Maize grains treated with botanicals, indicated that insect reproduction and development were impaired in all botanical pesticides. It is suggested that datura leaf, neem leaf powder can be used as good alternatives to chemical insecticides against S. zeamays due to their higher mortality, lower seed weight losses and higher germination capacity

Mid storage seed hardening: a mechanical method to maintain seed viability during long term jute seed preservation

Seed plays an important role in agricultural sector for both production and consumption purpose. Availability of vigour seed is one of the major constraints for maximizing crop production. However, healthy seed can also lose its viability during seed storage by changing different physio-chemical properties. Influence of environmental factors and seed containers during storage leading to seed deterioration. In this research, mid storage seed hardening treatment was applied in different aged seeds of jute species (C. Capsularis & C. olitorius) with two types of storage bags. Seed hardening treatment showed the less moisture content with better germination percentage compared to the untreated species of jute seeds. Seed packing in polythene bags during both short and long term seed storages had higher viable seeds compared to the cloth packing seeds. The effect of seed hardening treatment on seed oil content and pattern of oil degradation is distinct in early period of storage. The faster rate of oil degradation, soluble protein and free amino acids was found in seeds of un-treated stored seeds in cloth bag. Contrary, very slow rate of oil degradation was observed in harden seed and stored in polythene bag which indicated better storability of harden seeds

Petroleum Ether and Chloroform Soluble Fractions of Whole Plant Extract of Acanthus ilicifolis Linn. Possesses Potential Analgesic and Antioxidant Activities.

Background: Medicinal plants are the major sources of traditional treatment of disease and new drug discovery due to major side effects of synthetic drug. Objectives: The aim of study was to evaluate analgesic and antioxidant activities of petroleum ether and chloroform soluble fractions of whole plant extract of Acanthus ilicifoius. Materials and Methods: The plant extract, standard diclofenac, and distilled water as control was administered post orally in Swiss albino mice and observe the analgesic activity by acetic acid (0.6%) induced writhing method. The plant extract was also subjected to perform reducing power assay, DPPH free radical scavenging activity, and FRAP assay to evaluate antioxidant activity. Results: The pet ether, and chloroform soluble fraction of plant extract revealed significant analgesic activity on mice model. Notably, the pet ether and chloroform fraction showed (40.14 ± 2.32) % and (40.12 ± 0.9) % analgesic inhibition, whereas standard diclofenac revealed (52.79 ± 2.62) % analgesic inhibition. In antioxidant activity assay, the plant extract showed mild to moderate antioxidant activities compare to standard ascorbic acid. Conclusion: From the results, it could be concluded that, the pet ether and chloroform fractions of whole plant extract of A. ilicifolius possesses potential analgesic and antioxidant properties

Comprehensive Analysis to Uncover Determinants of Patient Appointment Compliance in Ophthalmology at the Kresge Eye Institute

Introduction: Appointment compliance (AC) has a significant impact on physician-patient relationship and overall patient care. However, determinants of AC in Ophthalmology and its subspecialties remains elusive. Methods: We performed a five-year retrospective analysis across Kresge Eye Institute (KEI) and its affiliated Michigan locations. A total of 597,364 appointments across \u3e13 subspecialties were included. AC was the primary outcome of interest. Compliant (CO) and non-compliant (NC) groups were compared to the following variables: patient characteristics (gender, race, age, insurance), appointment rank (relative to patient history), scheduling location, month, and ophthalmic specialty, in regard to arrival and no-show. Results: Among all appointments, 59.77% were associated with a female patient and 79.16% of the total number of appointments were compliant. AC differed concerning specialty, with retina representing the highest compliance across all appointments. Among 200+ insurance providers, Medicare was most frequently used and represented the highest share of CO appointments. African Americans were the primary ethnicity served by KEI and had the highest number of NC appointments. Conclusion: Our study demonstrates the impact of patient demographics, appointment characteristics, and ophthalmic subspecialty on AC. A better understanding of these determinants could allow for an increased CO for Ophthalmology practices

University Students’ and Teachers’ Wellbeing During COVID-19 in Bangladesh: A Qualitative Enquiry

The wellbeing of teachers and students has emerged as a common concern in research studies in recent times, specifically during the critical period of COVID-19. Based on the findings drawn from the qualitative data through focus group discussions of five groups of teachers (16 females and 8 males) and students (10 males and nine females) at the tertiary level of education in Bangladesh, this paper shows that online teaching during COVID-19 is affected by personal and social challenges, and consequently, both teachers and students experience anxieties and stresses. Teachers are anxious because of the university authorities\u27 surveillance, frequent pay cuts, and fear of losing jobs due to students\u27 low enrollment in universities. They also suffer from physical discomforts, such as back pain, blur vision, and headache because of the prolonged engagement with online activities. Students, especially those from a non-privileged background located in peripheral rural contexts, seem to suffer more from contextual realities that are non-conducive for technology-based learning. Increased numbers and various forms of online assessments also seem to become a burden for them. In general, educational experiences of online teaching seemed to have a peripheral role in their conceptualization of wellbeing. The paper concludes that the insurmountable attention given to online pedagogic practices across the world needs to be balanced out by an equal effort in improving the wellbeing of both teachers and students