9 research outputs found
2-Chloro-5-nitroaniline
No full textThe molecule of the title compound, C6H5ClN2O2, is close to being planar (rms deviation = 0.032 Å for all non-H atoms), with a maximum deviation of -0.107 (3) Å for an O atom. In the crystal structure, intermolecular N-H...O and N-H...N interactions link the molecules into a three-dimensional network. Key indicators: single-crystal X-ray study; T = 173 K; mean σ(C–C) = 0.002 A°; R factor = 0.023; wR factor = 0.061; data-to-parameter ratio = 11.8
Acceptance of a virtual coach for quitting smoking and becoming more physically active: A thematic analysis: Traits for a virtual coach to be a ”friend”
No full textSeeing the virtual coach as a friend is beneficial as it increases the motivation, confidence, and perseverance of the accompanying. Here, an investigation has taken place to what characteristics the virtual coach must possess to establish this friendly relationship. Thus, the main research question is: What are the reasons for seeing the virtual coach as a stranger or friend? This research made use of pre-gathered data. Here, five hundred participants interacted with the text-based virtual coach Sam in five separate sessions. Afterwards, each participant rated the relationship with the virtual coach, followed by an explanatory free-text response to which thematic analysis was applied. This resulted in five main themes: Relation, Positive Characteristics, Perception, Impersonal, and Chat Opinions. These were used to determine the characteristics the virtual coach must have to be considered a friend. Furthermore, these themes were used to obtain correlations. With these, it has been concluded that the user is more likely to develop a closer relationship with the virtual coach when: perceiving it as a human, pleasantly conversing, and being positive about its character. Whereas the user's age has a negligible influence on the relationship.This research is based on a study conducted by Albers and Brinkman, and is part of the Perfect Fit Project.CSE3000 Research ProjectComputer Science and Engineerin
A Stylistic Forensic Analysis of Mahira’s Suicade Notes
No full textThis research aims to analyze forensic stylistics which depicts a female student who left a suicide note. This research not only focuses on stylistic forensic analysis, but also deals with linguistic elements and their influence on the social environment. This research uses qualitative methods. The focus of stylistic analysis in a forensic context is the understanding and interpretation of language that is difficult to understand. The content of the forensic linguistic text of a student's suicide note is a problem regarding writing that is not appropriate to the context, therefore this research also proposes several main categories of writing, namely writing discrimination, author identification, author characterization, and determination of author intent. Apart from that, the vocabulary used in these notes is not usually spoken by Mahira
Taman Labirin Bubutan Dan Exhibition Center
No full textPandemi COVID-19 yang masih terus berlanjut semakin membuat manusia harus berjauhan satu sama lain. Hal tersebut berlawanan dengan sifat alamiah manusia yang merupakan makhluk sosial, dimana membutuhkan orang lain dan memerlukan interaksi. Pandemi COVID-19 sendiri yang sudah memasuki tahun kedua sejak tulisan ini pertama kali disusun, kian tidak menunjukkan akhirnya dikarenakan grafik yang terus meningkat mengingat baru saja memasukin gelombang lonjakan yang kedua. Penulis khawatir jika pandemi yang tidak berujung ini akan membuat manusia semakin individualis dan tidak lagi berkumpul selayaknya sifat alamiah mereka. Maka dari itu, penulis merasa perlu untuk melakukan penyesuaian terhadap ruang publik dalam menghadapi kehidupan pasca pandemi. Penyesuaian yang dilakukan menggunakan kombinasi dari beberapa teori serta evaluasi yang dilakukan terhadap ruang publik di masa pandemi. Dari beberapa teori serta hasil evaluasi tersebut kemudian didapatkan kriteria desain yang dikombinasikan dengan aspek-aspek terkait ruang publik agar dapat memenuhi kebutuhan pengunjung ketika masa pandemi selesai dan menyesuaikan agar manusia kembali kepada sifat alamiahnya
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The ongoing COVID-19 pandemic is making people have to be far away from each other. This is contrary to human nature which is a social creature, which requires other people and requires interaction. The COVID-19 pandemic itself, which has entered its second year since this article was first compiled, is increasingly showing no end due to the ever-increasing graph considering that it has just entered the second wave of spikes. The author is worried that this endless pandemic will make humans more individualistic and no longer gather as they are in nature. Therefore, the author feels the need to make adjustments to the public sphere in dealing with postpandemic life. Adjustments were made using a combination of several theories as well as evaluations carried out on public spaces during the pandemic. From several theories and the results of these evaluations, design criteria are then obtained which are combined with aspects related to public spaces in order to meet the needs of visitors when the pandemic period is over and adjust so that humans return to their natural nature
N-(4-Methoxyphenyl)pivalamide
No full textIn the title molecule, C12H17NO2, the amide (N—C=O) plane is oriented at an angle of 33.9 (1)° with respect to the aromatic ring. This is accompanied by an intramolecular C—H...O hydrogen bond. The methoxy group lies almost in the plane of the benzene ring [C–O–C–C torsion angle = 2.7 (2)°]. In the crystal structure, intermolecular N—H...O hydrogen bonds link the molecules into chains along [010]
N-(4-Chlorophenyl)-3,4,5-trimethoxybenzamide
No full textIn the title compound, C16H16ClNO4, the dihedral angle between the two aromatic rings is 67.33 (8)°. The crystal packing shows strong intermolecular N—H...O hydrogen bonds that link the molecules to form chains along [overline{1}01]
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Technological impact on the art of moviemaking: deploying new and convergent media to redefine a model for Pakistan’s cinema
No full textThis thesis examines the decline in Pakistani cinema during the last two decades. It examines the history of the cinema and exposes some possible, previously ignored, causes for that decline. This research led the author to ask “Can new and convergent media be helpful in reviving the Pakistani cinema?” The thesis introduces the ideas of established and emergent cinema, building on the work of Williams (1977) in discussing the ideas of dominant, residual and emergent culture. The exploration reveals two gaps in the film industry: first, the lack of training in the making of films; and, second, the change in possible production methods allowed by new and emergent technologies. The thesis addresses both of these gaps by suggesting new production paradigms which incorporate the new technology and by examining two scripts to develop methodologies for teaching. The scripts are produced into films as the practice section of the research. The first film, creative element 1, is developed using some of the new tehnologies, students as crew and the available resources of an educational establishment to test the methodologies that have been derived. The outcomes of the creative element 1 laid the foundation of the second film, creative element 2. It is shot on mobile phones and distributed from Pakistan through Vimeo with a negligible budget. The social networks helped to arrange equipment and locations and allowed extreme freedom to the filmmaker
Seeds of Giant Dodder (Cuscuta reflexa) as a Function of Extract Procedure and Solvent Nature
No full textSeeds of a renowned medicinal plant, giant dodder (Cuscuta reflexa), were assessed to appraise the effect of solvent and extraction technique variation on antioxidants potential. Dodder seed, also called cuscuta seed, has been considered superb tonic in traditional herbal medication for eyes, liver, spleen and kidney. Results show that selected solvent and procedure plays a key role in the composition and activity of extractable material. Three extraction procedures Orbital shaker, Decoction and Ultrasonic assisted extraction and five different solvents n-hexane, ethyl acetate, 100% methanol, 80% methanol and 60% methanol were used to get optimized conditions. Total phenolic and flavonoids content were found maximum in the extracts of aqueous organic system containing 80% methanol in Ultrasonic assisted extraction method but in case of tannins ethyl acetate and Orbital shaker extraction was found more suitable partner. Antioxidant estimation assays showed a little bit variation as DPPH and ABTS exhibited maximum inhibition in 80% methanol and Ultrasonic assisted extraction but 100% methanol was found better for FRAP assay. Decoction results were mostly in between the both Orbital shaker and Ultrasonic assisted extraction. Overall results indicate that coexistence of polar solvents and Ultrasonic assisted extraction gives a better choice for extractability of potent antioxidants from seeds. HPLC analysis confirmed presence of valuable phenolic acids. Pearson’s correlation coefficient reveals a significant relationship between extracted components and antioxidant capacity P< 0.05 or 0.01.</jats:p
Performance Evolution for Sentiment Classification Using Machine Learning Algorithm
No full text[EN] Machine Learning (ML) is an Artificial Intelligence (AI) approach that allows systems to adapt to their environment based on past experiences. Machine Learning (ML) and Natural Language Processing (NLP) techniques are commonly used in sentiment analysis and Information Retrieval Techniques (IRT). This study supports the use of ML approaches, such as K-Means, to produce accurate outcomes in clustering and classification approaches. The main objective of this research is to explore the methods for sentiment classification and Information Retrieval Techniques (IRT). So, a combination of different machine learning algorithms is used with a dataset from amazon unlocked mobile reviews and telecom tweets to achieve better accuracy as it is crucial to consider the previous predictions related to sentiment classification and IRT. The datasets consist of user reviews ratings and algorithms utilized consist of K-Means Clustering algorithm, Logistic Regression (LR), Random Forest (RF), and Decision Tree (DT) algorithms. The amalgamation of each algorithm with the K-Means resulted in high levels of accuracy. Specifically, the K-Means combined with Logistic Regression (LR) yielded an accuracy rate of 99.98%. Similarly, the K-Means integrated with Random Forest (RF) resulted in an accuracy of 99.906%. Lastly, when the K-Means was merged with the Decision Tree (DT) Algorithm, the accuracy obtained was 99.83%.We exhibited that we could foresee efficient, effective, and accurate outcomes.Hassan, F.; Qureshi, NA.; Khan, MZ.; Khan, MA.; Soomro, AS.; Imroz, A.; Marri, HB. (2023). Performance Evolution for Sentiment Classification Using Machine Learning Algorithm. 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