The use of slang, abusive, and offensive language has become common practice on social media. Even though social media companies have censorship polices for slang, abusive, vulgar, and offensive language, due to limited resources and research in the automatic detection of abusive language mechanisms other than English, this condemnable act is still practiced. This study proposes USAD, a lexicon-based intelligent framework to detect abusive and slang words in Perso-Arabic-scripted Urdu Tweets. Furthermore, due to the nonavailability of the standard dataset, we (...) also design and annotate a dataset of abusive, offensive, and slang word Perso-Arabic-scripted Urdu as our second significant contribution for future research. The results show that our proposed USAD model can identify 72.6% correctly as abusive or nonabusive Tweet. Additionally, we have also identified some key factors that can help the researchers improve their abusive language detection models. (shrink)

_Textile sector of Pakistan is one of the great contributors in country’s economy, and also the key contributor in making the environment polluted. Textiles have lengthy and complex supply chains (SC) which have crucial role in sustainability. Energy intensive business processes, excessive use of water and hazardous chemicals, use of synthetic yarns and fibers, make it crucial to implement sustainable practices in SC of textile industries. Pakistani textile sector does not fully adopt the sustainable practices that are being used around (...) the world and it is not immediately clear to what extent the practices used in the local industry benefit the environment. The objective of this study is the analysis of ongoing sustainable practices of Yunus Textile Mills (YTM), impact of those sustainable practices and review of international sustainable practices that can be implemented at YTM. In this research quantitative and qualitative research methods have been used along with Triple Bottom Line Approach of Sustainability. Data gathered through business publication, onsite surveys & interviews. Results obtained from the study shows that sustainable practices used by Yunus textile have positive impact on environment._. (shrink)

Professor D. Z. Phillips in ‘Bad Faith and Sartre's Waiter’ assigns to Sartre the view that ‘waiters are necessarily in bad faith’, i.e. the profession of waiting as such is in bad faith. What could this mean in the context of Sartre's philosophy? That waiters as a class seek to flee their freedom by adopting that vocation? It must mean something on those lines since, for Sartre, to engage in bad faith is to deny one's freedom. The question then arises: (...) could Sartre have heldsuch a view ? And, if he could not have, how does Phillips manage tothink he did ? (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to preserve privacy. Previously, (...) we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)

The question of the development of aesthetic perception in relation to works of art and phenomena of nature suggests a differentiation between aesthetic education and art education which will be attempted in this study. At the same time the necessary interrelationship between the two will also be analysed.

Computer vision and human–computer interaction are essential in many technological fields. Researchers in CV are particularly interested in real-time object detection techniques, which have a wide range of applications, including inspection systems. In this study, we design and implement real-time object detection and recognition systems using the single-shoot detector algorithm and deep learning techniques with pre-trained models. The system can detect static and moving objects in real-time and recognize the object’s class. The primary goals of this research were to investigate (...) and develop a real-time object detection system that employs deep learning and neural systems for real-time object detection and recognition. In addition, we evaluated the free available, pre-trained models with the SSD algorithm on various types of datasets to determine which models have high accuracy and speed when detecting an object. Moreover, the system is required to be operational on reasonable equipment. We tried and evaluated several deep learning structures and techniques during the coding procedure and developed and proposed a highly accurate and efficient object detection system. This system utilizes freely available datasets such as MS Common Objects in Context, PASCAL VOC, and Kitti. We evaluated our system’s accuracy using various metrics such as precision and recall. The proposed system achieved a high accuracy of 97% while detecting and recognizing real-time objects. (shrink)

Efficient community detection in a complex network is considered an interesting issue due to its vast applications in many prevailing areas such as biology, chemistry, linguistics, social sciences, and others. There are several algorithms available for network community detection. This study proposed the Sigmoid Fish Swarm Optimization algorithm to discover efficient network communities. Our proposed algorithm uses the sigmoid function for various fish moves in a swarm, including Prey, Follow, Swarm, and Free Move, for better movement and community detection. The (...) proposed SiFSO algorithm’s performance is tested against state-of-the-art particle swarm optimization algorithms in Q-modularity and normalized mutual information. The results showed that the proposed SiFSO algorithm is 0.0014% better in terms of Q-modularity and 0.1187% better in terms of NMI than the other selected algorithms. (shrink)

This abstract presents a novel brain-computer interface (BCI) framework to control a prosthetic leg, for the rehabilitation of patients suffering from locomotive disorders, using functional near-infrared spectroscopy (fNIRS). fNIRS signals corresponding to walking intention and rest are used to initiate and stop the gait cycle and a nonlinear proportional derivative computed torque controller (PD-CTC) with gravity compensation is used to control torques of hip and knee joints for minimization of position error. The brain signals of walking intention and rest tasks (...) are acquired from primary motor cortex in the left hemisphere for nine subjects. After acquiring brain signals, in order to remove motion artifacts and physiological noises, the performance of six different filters i.e. Kalman, Wiener, Gaussian, hemodynamic response filter (hrf), Band-pass and finite impulse response, is evaluated. Afterwards, six different features are extracted from oxygenated hemoglobin signals and their different combinations were used for classification. The classification performance of five different classifiers i.e. artificial neural network, quadratic discriminant analysis, linear discriminant analysis (LDA), Naïve Bayes and support vector machine (SVM) is used. The classification accuracies obtained from SVM using hrf filter are significantly higher (p < 0.005) than the other combinations of classifier and filters. These accuracies are 77.5%, 72.5%, 68.3%, 74.2%, 73.3%, 80.8%, 65%, 76.7%, and 86.7% for all nine subjects. The control commands generated using classifier initiate and stop the gait cycle of the prosthetic leg whose knee and hip torques are controlled using PD-CTC to minimize position error. The proposed scheme can be effectively used for neurofeedback training and rehabilitation of lower limb amputation of paralyzed patients. (shrink)

Landslide is a critical natural geological hazard that causes severe damage to property, infrastructure, and humans. In general, some location-specific factors trigger a landslide. Wireless sensor network is an enabling technology to monitor most of the parameters associated with these factors. A challenge in landslide monitoring through WSN is that each sensed data item might be critical whereas the underlying wireless communication is often unreliable. In case of landslides, the terrains have irregular shapes, providing harsh conditions for wireless communication thereby (...) more data loss may be expected. This study focuses on the effect of lossy communication in WSN on the efficiency and accuracy of landslide monitoring systems. To this end, collaborative local data analysis is used to enable each node to decide locally whether its sensed data corresponds to a potential event-of-interest. Through extensive simulations, the performance of various landslide prediction and detection models has been evaluated. By and large, the study lets a significant insight into landslide monitoring before implementing a parameterized application for real-world deployment. (shrink)

IntroductionThe COVID-19 pandemic has led to unprecedented strain to healthcare systems worldwide and posed unique challenges to the healthcare professionals and the general public.ObjectivesThe aim of this study is to evaluate the impact of COVID-19 on the mental health, behavioral, and physical wellbeing of HCPs in the early and mid-term periods of the pandemic in comparison to non-HCPs. Thus, facilitating and guiding optimum planning and delivery of support to HCPs.Methods and AnalysisAn observational cross-sectional survey and cohort study aiming to enroll (...) over 1050 participants. Study questionnaires will be completed at baseline and after 6-weeks and 4-months. Recruitment initiated July 2020. The study was designed in London, United Kingdom, but open to participants worldwide. Baseline: Questionnaires comprising of validated self-administered screening tools for depression, anxiety, sleep-related issues, wellbeing, and burnout. The questionnaires also explore changes in behavior and physical wellbeing of the participants. In addition, associations of these mental health and behavioral factors with work-related factors and support will be explored. Six-weeks and 4-months follow-up: Follow-up questionnaires will assess change in symptoms of anxiety and depression, sleep disorders, use of alcohol and other substances, behavioral or interpersonal relationship changes. Physical wellbeing will be assessed through the presence of suspected or confirmed COVID-19 infection and absence from work. We will also evaluate the impact of variable provision of personal protection equipment, extended working hours, and concern for the wellbeing of family members, anxiety levels, and evidence of burnout.Statistical ConsiderationsThe study has 80% power to detect a 10% difference of combined depression and/or anxiety symptoms between the groups using two-sided type 1 error at 0.05 at baseline. Assuming that only 50% of these HCPs agree to be a part of a cohort survey, we will have 80% power to detect around 12% difference in the two groups in reported physical symptoms, or prevalence of depression and/or anxiety at the end of the study.EthicsThe study was approved by the Cambridge East, Research Ethics Committee.Trial Registration NumberClinicalTrials.gov, NCT04433260. (shrink)

Drawing on the scholarship of Critical Religion, this article shows how the modern category “religion” operates through a gender code which upholds its discursive power and enables the production of religious—and therefore racial—hierarchies. Specifically, it argues that mentioning religion automatically makes gender present in discourse. Acknowledging religion as an inherently gendered category in this way gives further insight into the discursive power and functioning of the religious label. With the example of the Westphalian production of the “myth of religious violence” (...) and the employment of “religion” in colonial contexts, I demonstrate how a gender code upholds and enables the discursive power of religion. Religion is both gendered and gendering. Acknowledging the multiple ways in which religion is gendered and gendering, then, has important bearings on the analysis of religion’s racializing function which is upheld and aided by the gender code through which religion is spoken. (shrink)

This work identifies the influence of chaos theory on fractional calculus by providing a theorem for the existence and stability of solution in fractional-order gyrostat model with the help of a fixed-point theorem. We modified an integer order gyrostat model consisting of three rotors into fractional order by attaching rotatory fuel-filled tank and provided an iterative scheme for our proposed model as a working rule of obtained analytical results. Moreover, this iterative scheme is injected into algorithms for a system of (...) integer order dynamical systems to observe Lyapunov exponents and a bifurcation diagram for our proposed fractional-order dynamical model. Furthermore, we obtained five equilibrium points, including four unstable spirals and one saddle node, using local dynamical analysis which acted as self-exciting attractors and a separatrix in a global domain. (shrink)

The New Towns Movement began in England and later spread world-wide in response to the increasing concern felt at the deterioration of the quality of life in the large cities under the impact of industrialization. The New Towns, it was felt, would combine the advantages of life in the country with that of life in the city. They would be small communities of between 30.000 and 60.000 inhabitants. Their principal characteristics were to be a balanced economy and a well-defined pattern (...) of industrial, commercial and residential zones. (shrink)

Acute Myeloid Leukemia is a kind of fatal blood cancer with a high death rate caused by abnormal cells’ rapid growth in the human body. The usual method to detect AML is the manual microscopic examination of the blood sample, which is tedious and time-consuming and requires a skilled medical operator for accurate detection. In this work, we proposed an AlexNet-based classification model to detect Acute Myeloid Leukemia in microscopic blood images and compared its performance with LeNet-5-based model in Precision, (...) Recall, Accuracy, and Quadratic Loss. The experiments are conducted on a dataset of four thousand blood smear samples. The results show that AlexNet was able to identify 88.9% of images correctly with 87.4% precision and 98.58% accuracy, whereas LeNet-5 correctly identified 85.3% of images with 83.6% precision and 96.25% accuracy. (shrink)

Le cannabis est envisagé ici comme un instrument de la politique d’aménagement des territoires, au sens où R. Neuburger évoque les territoires de l’intime. Ceci permet la création de nouvelles narrations qui permettent de sortir de l’impasse où le cannabis est le problème pour les parents alors que c’est la solution pour le jeune. Deux vignettes cliniques illustrent cette métaphore et les opportunités qu’elle offre pour la thérapie.