Data Analytics for Google Trend Search Result of Illness Symptoms

The outbreak of COVID-19 has escalated from March 2020. Since then, people from all over the world are curiously searching different types of illness symptoms including corona virus. Before the outbreak, people were also searching different types of symptoms at different times. Both diseases share same symptoms, but in the flu season. If certain types of symptoms are visible at summer season, then these symptoms are for corona virus. The main purpose of our study is to find out this discriminative information from these search result. We will discuss some mathematical concepts and then develop an algorithm based on those formulas and then apply this algorithm to those datasets to find out those discriminative data

Enigma of Partition Depicted in Bapsi Sidhwa’s Ice-Candy-Man

The tragedy of Partition provided writers with the occasion to write about the plight of the people of the subcontinent and to bring home the point of the impact of British rule, which had previously boasted of a “civilizing mission”. The vast volume of Partition fiction in English, Urdu, Hindi, Bengali, and other languages of the subcontinent faithfully record the gruesome human disaster in the wake of Partition. The incredible suffering and bewilderment of the people of the subcontinent have been a favourite theme with Indian and Pakistani writers. Public frenzy, communal hatred, extreme disintegration, and large-scale sectarian violence are some of the critical issues amply found in the works of Khushwant Singh’s Train to Pakistan (1956), Attia Hosain’s Sunlight on a Broken Column (1961), Rahi Masoom Raza’s Adha Gaon (1966), Bhisham Sahni’s Tamas (1973), Amitav Ghosh’s The Shadow Lines (1988), Bapsi Sidhwa’s Ice-Candy-Man (1991), short stories by Saadat Hassan Manto, and the poems of Faiz Ahmed Faiz. In her novel Ice-Candy-Man (1991), Bapsi Sidhwa narrates the story of an upheaval of the 1947 partition of India through the eyes of a young Parsee girl Lenny growing up in Lahore. The character of Ayah is introduced to refer to the several millions of displaced, looted, and raped Hindus and Muslims during one of the harshest political phases in the subcontinent’s history. This paper endeavours to portray the trauma of communal violence as depicted by Bapsi Sidhwa in her novel, Ice-Candy-Man

Interplay of Fantasy and Realism in Salman Rushdie’s Midnight’s Children

Fantasy and realism are the traits to be found in every culture and individual. Fantasy was often dismissed for being a thing associated with children. This was a practice found to be rampant in the past or it was rather a matter of the past so to say. After centuries of oblivion, people have started giving importance to fantasy when there is a lot of chaos in the society. Fantasy as a genre that helps us to band together, explain, change and form an opinion on reality. Fantasy can surely tempt the human desire, for more than the familiar world of the readers, into ease, anyway from reality and communicate with immense imagination that the readers can connect to. With this in mind, the paper tries to analyze Rushdie’s Midnight’s Children the bizarre and the fantastic blurs the boundaries between the real and plausible in the novel, thereby problematizing the identities of gender, parenthood, and nationality, and renders the readers into a state of uncertainty by incorporating oblique references or links. It also aims to critically analyze and discuss how the lines between fantasy and reality are blurred in literature. The importance of this study is to connect the fine line of fantasy with reality in literature and to present perceptions to the readers on how literature is understood differently by different people

Investigation of the chemical profiles of seven wood species for their potential applications

Determination of the chemical composition of biomaterial is important for their valued utilization in biorefinery. In this study, the chemical composition of seven wood species, i.e. lambu (Khaya anthotheca), raj-koroi (Albizia richardiana), jhau (Casuarina equisetifolia), sil-koroi (Albizia procera), katbadam (Terminalia catappa), jolpai (Elaeocarpus robustus), and arjun (Terminalia arjuna) were examined. The chemical characterization of these wood species can expedite a further study on the extraction of cellulose, lignin, and extractive. alpha-cellulose content was in the range of 37.0% to 42.1% and lignin content was 20.4% to 34.1%. The solubility in 1% caustic soda was 16.1% to 24.3%. The a-cellulose and lignin content were similar to other wood species. Therefore, these species can be a potential source of raw material for biorefinery

Investigation of the potentiality of five bamboo species in biorefinery through analysis of chemical profiles

Determination of the chemical composition of biomaterial is important for their valued utilization in biorefinery. In this study, the chemical composition of five bamboo species, i.e., mitinga (Bambusa tulda), borak (Bambusa balcooa), rengoon (Thyrsostachys oliveri), orah (Dendrocalamus longispathus), and bajja (Bambusa vulgaris) were determined. The chemical characterization of these bamboo species can expedite a further study on the extraction of cellulose and lignin. alpha-cellulose content was in the range of 42.7-45.7% and Klason lignin content was 22.4-28.2%. The ash content was 1.8-4.3% for the studied five bamboo species. The alpha-cellulose and lignin content were similar to other non-timber spices. The ash content was lower than other non-timber species. Therefore, these species can be a potential source of raw material for biorefinery

Paraphernalia of Growth Regulators During In Vitro micro-Propagation of Grapevine (Vitis vinifera L.) from Shoot Tips and Nodal Segments

Abstract: As grapevine (Vitis vinifera L.) is rarely produced in Bangladesh because of unavailability of improved varieties, so this study was designed to solve this problem through evaluating the effects of hormonal combination for the duration of in vitro micro propagation of grapevine (Vitis vinifera L.) from shoot tips and nodal segments. Firstly, surface sterilization process was carried out by using HgCl 2 (mercuric chlorite) at 0.1% for 3 min and best result was found. During establishment stage, explants were cultured on MS (Murashige and Skoog) basal medium supplemented with BAP (6-benzylamino purine) 0.5, 1.0 and 2.0 mg/l and NAA (β-naphthalene acetic acid). 0.1mg/l where MS+ BAP 1.0 mg/l + NAA 0.1mg/l displayed best potential result. During shoot multiplication stage, BAP 2.0 and 3.0 mg/l and NAA 0.1, 0.2 and 0.3 mg/l and their combination were used and highest number of proliferated shoots was obtained from MS+ BAP 3.0 mg/l + NAA 0.2 mg/l. For rooting stage, NAA 0.5 and 1.0 mg/l and IBA (Indol-3-butyric acid) 0.5, 1.0 and 1.5 mg/l were used and tested. The highest rooting percentage, number of roots per shoot and root length found in MS+ 0.5 mg/l NAA + IBA 1.0 mg/l. Finally, neo-formed plantlets were transferred into pots containing peat moss and sand (1:1 v/v) and potential growth of these plantlets in environment indicates that through using the adequate amount of hormonal combination could give a better solution for the improvement and availability of grapevine (Vitis vinifera L.) for Bangladeshi farmers

DOSTUPNOST MORSKIH RIBA NA COX’S BAZARU U BANGLADEŠU: STUDIJA SLUČAJA O ISKRCAJNOM CENTRU BFDC

Fish availability in the coastal landing center highlights the assumption of stocks in the marine fishing zone of the ocean. This study, therefore, aimed to analyze the availability of marine fishes in the Bangladesh Fisheries Development Corporation (BFDC) landing center, Cox’s Bazar, Bangladesh between January 2021 and May 2021. A total of 54 species were recorded, of which 42 were marine fishes, 7 were shellfishes and 5 were large fishes. The dominant orders were Perciformes (56%), Scombriformes (17%) and Clupeiformes (10%). More than 56% of the total marine fishes were classified as Least Concern, nearly 10% were categorized as Near Threatened and 2% were marked Vulnerable. The dominant orders of shellfish were Portunidae (43%), followed by Penaidae (29%), Loligonidae (14%) and Octopopidae (14%). Shrimp Penaeous monodon had the highest consumer demand, whereas consumer demand for non-conventional shellfish was comparatively low. Most of the shellfish were categorized as Least Concern. Among large fishes, the wider availability of sharks (five species) and rays (two species) was observed in the winter and monsoon season, although the consumer demand for those large fishes was low. The Vulnerable sharks and rays were Sphyma zygaena and Mobula birostris. This study elucidates the present scenario of marine fishes in the BFDC fish landing center, Cox’s Bazar, Bangladesh.Dostupnost ribe u obalnom iskrcajnom centru naglašava pretpostavku o stokovima u zoni morskog ribolova u oceanu. Cilj ovog istraživanja je analizirati dostupnost morskih riba u iskrcajnom centru BFDC na Cox’s Bazaru u Bangladešu u razdoblju od siječnja do svibnja 2021. godine. Zabilježene su ukupno 54 vrste, od kojih su 42 morske ribe, 7 školjkaša i 5 velikih riba. Dominantni redovi su Perciformes (56%), Scombriformes (17%) i Clupeiformes (10%). Više od 56% ukupne morske ribe klasificirano je kao najmanje zabrinjavajuće vrste, a za razliku od toga, gotovo 10% morskih riba je gotovo ugroženo, a 2% je ranjivo. Dominantni redovi školjkaša su Portunidae (43%), zatim Penaidae (29%), Loligonidae (14%) i Octopopidae (14%). Penaeous monodon je najviše tražena od potrošača, dok je potražnja potrošača za nekonvencionalnim školjkama relativno niska. Većina školjkaša je iz skupine najmanje zabrinjavajućih vrsta. Među velikim ribama, razmjerno veća dostupnost morskih pasa (5 vrsta) i raža (2 vrste) uočena je zimi i u razdoblju monsuna, iako je potražnja potrošača za tom megafaunom niska. Ranjivi morski psi i raže su Sphyma zygaena i Mobula birostris. Ova studija analizira trenutni sastav morskih riba u iskrcajnom centru BFDC na Cox\u27s Bazaru u Bangladešu

Fault Ride Through Capability Improvement of DFIG Based Wind Farm Using Nonlinear Controller Based Bridge-Type Flux Coupling Non-Superconducting Fault Current Limiter

High penetration of Doubly Fed Induction Generator (DFIG) into existing power grid can attribute complex issues as they are very sensitive to the grid faults. In addition, Fault Ride Through (FRT) is one of the main requirements of the grid code for integrating Wind Farms (WFs) into the power grid. In this work, to enhance the FRT capability of the DFIG based WFs, a Bridge-Type Flux Coupling Non-Superconducting Fault Current Limiter (BFC-NSFCL) is proposed. The effectiveness of the proposed BFC-NSFCL is evaluated through performance comparison with that of the Bridge-Type Fault Current Limiter (BFCL) and Series Dynamic Braking Resistor (SDBR). Moreover, a dynamic nonlinear controller is also proposed for controlling the operation of the BFC-NSFCL. Extensive simulations are carried out in the MATLAB/SIMULINK environment for both symmetrical and unsymmetrical temporary as well as permanent faults. Based on the simulation results and different numerical analysis, it is found that the proposed nonlinear controller based BFC-NSFCL is very effective in enhancing the FRT capability of the WF. Also, the BFC-NSFCL outperforms the conventional BFCL and SDBR by maintaining a near-seamless performance during various grid fault situations

Data-Driven State Estimation for Improved Wide Area Situational Awareness in Smart Grids

Wide area situational awareness (WASA) in smart grids includes automatic monitoring, perception and detection of anomalies in these systems. The goal of WASA is to make smart grids aware of their physical and operational state for more effective operational decisions and control. As such, tracking the system\u27s state or state estimation is one of the key objectives of WASA. The extensive integration of cyber elements into smart grids, such as large deployment of various monitoring and measurement devices, provides new opportunities to improve WASA. However, the tight coupling of power grids with cyber components introduces vulnerabilities to cyber and physical stresses. State estimation is one of the key functions in WASA. The conventional state estimators have been widely deployed in utility control centers to help with monitoring the state of the system. However, traditional model-based state estimation methods do not adequately meet the real-time monitoring and accuracy requirements for smart grids. Many of the model-based state estimation techniques are based on steady-state analysis, which cannot be accurate for modern power systems due to highly dynamic and stochastic variations introduced by, for instance, distributed energy generations and fast-changing loads. The availability of large volume of measurement data in smart grids has opened new directions to complement the traditional state estimation techniques using data-driven state estimation methods. In this dissertation, data-driven state estimation techniques are developed to support the WASA functions, such as monitoring the state of the system and detecting cyber and physical stresses in the system. The presented data-driven and machine learning models include linear Minimum Mean Square Error (MMSE) estimation, Bayesian Multivariate Linear Regression (BMLR) combined with Auto-Regressive AR(p) process, and Kalman filters and Temporal Graph Convolution Neural Networks (T-GCNNs). In addition to the measurement data, the T-GCNN can learn the features in the non-Euclidean domain of the system’s topology, which can capture the structures and interactions among the components of power grids. The performance of the proposed techniques are evaluated using simulated power system measurement data under various normal and stressed scenarios. Moreover, low latency data processing is important for real-time WASA in smart grids. Distributed and local processing of data is a promising strategy that can improve system monitoring tasks, as it satisfies the low latency requirements while avoiding the enormous overhead of transferring a huge volume of time-sensitive data to central processing units. Distributed data processing may improve the efficiency of many tasks and one such task is state estimation in power systems. In this dissertation, multi-region distributed state estimation is modeled and analyzed under various information sharing techniques among the regions. The regions in the system are defined based on physical distance and the correlation among the state of the components. Several data-driven and machine learning models for centralized and distributed state estimation are evaluated for the system with respect to the various ways of information sharing techniques. It is discussed that the multi-region distributed state estimation can achieve comparable performance to centralized techniques with reduced communication and computation cost