Search results for: automatic classification

Authors: Yuan-Hao Lee, Chia-Wei Lee, Ming-Fang Lin, Tzu-Huei Wu, Chih-Hsiang Ko, Wing P. Chan

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Computed tomography (CT) scan of the head is a good method for investigating cranial lesions. However, radiation-induced oxidative stress can be accumulated in the eyes and promote carcinogenesis and cataract. In this regard, we aimed to protect the eyes with barium sulfate shield(s) during CT scans and investigate the resultant image quality and radiation dose to the eye. Patients who underwent health examinations were selectively enrolled in this study in compliance with the protocol approved by the Ethics Committee of the Joint Institutional Review Board at Taipei Medical University. Participants’ brains were scanned with a water-based marker simultaneously by a multislice CT scanner (SOMATON Definition Flash) under a fixed tube current-time setting or automatic tube current modulation (TCM). The lens dose was measured by Gafchromic films, whose dose response curve was previously fitted using thermoluminescent dosimeters, with or without barium sulfate or bismuth-antimony shield laid above. For the assessment of image quality CT images at slice planes that exhibit the interested regions on the zygomatic, orbital and nasal bones of the head phantom as well as the water-based marker were used for calculating the signal-to-noise and contrast-to-noise ratios. The application of barium sulfate and bismuth-antimony shields decreased 24% and 47% of the lens dose on average, respectively. Under topogram-based TCM, the dose saving power of bismuth-antimony shield was mitigated whereas that of barium sulfate shield was enhanced. On the other hand, the signal-to-noise and contrast-to-noise ratios of DSCT images were decreased separately by barium sulfate and bismuth-antimony shield, resulting in an overall reduction of the CNR. In contrast, the integration of topogram-based TCM elevated signal difference between the ROIs on the zygomatic bones and eyeballs while preferentially decreasing the signal-to-noise ratios upon the use of barium sulfate shield. The results of this study indicate that the balance between eye exposure and image quality can be optimized by combining eye shields with topogram-based TCM on the multislice scanner. Eye shielding could change the photon attenuation characteristics of tissues that are close to the shield. The application of both shields on eye protection hence is not recommended for seeking intraorbital lesions.

Keywords: computed tomography, barium sulfate shield, dose saving, image quality

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Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

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Authors: Thilini Hathurusinghe, Uthpalie Siriwardhana, W. M. Ediri Arachchi, Ranga Thudugala, Indeewari Herath, Gayani Senanayake

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The foramen magnum is more prone to protect than other skeletal remains during high impact and severe disruptive injuries. Therefore, it is worthwhile to explore whether these measurements can be used to determine the human gender which is vital in forensic and anthropological studies. The idea was to find out the ability to use quantitative measurements of foramen magnum as an anatomical indicator for human gender estimation and to evaluate the gender-dependent variations of foramen magnum using quantitative measurements. Randomly selected 113 subjects who underwent CT head scans at Sri Jayawardhanapura General Hospital of Sri Lanka within a period of six months, were included in the study. The sample contained 58 males (48.76 ± 14.7 years old) and 55 females (47.04 ±15.9 years old). Maximum length of the foramen magnum (LFM), maximum width of the foramen magnum (WFM), minimum distance between occipital condyles (MnD) and maximum interior distance between occipital condyles (MxID) were measured. Further, AreaT and AreaR were also calculated. The gender was estimated using binomial logistic regression. The mean values of all explanatory variables (LFM, WFM, MnD, MxID, AreaT, and AreaR) were greater among male than female. All explanatory variables except MnD (p=0.669) were statistically significant (p < 0.05). Significant bivariate correlations were demonstrated by AreaT and AreaR with the explanatory variables. The results evidenced that WFM and MxID were the best measurements in predicting gender according to binomial logistic regression. The estimated model was: log (p/1-p) =10.391-0.136×MxID-0.231×WFM, where p is the probability of being a female. The classification accuracy given by the above model was 65.5%. The quantitative measurements of foramen magnum can be used as a reliable anatomical marker for human gender estimation in the Sri Lankan context.

Keywords: foramen magnum, forensic and anthropological studies, gender estimation, logistic regression

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Authors: Asaiel Mubark Al Hadi

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Background: A frequent anorectal condition known as hemorrhoids, sometimes known as piles, is characterized by a weakening of the anal cushion and the supporting tissue as well as spasms of the internal sphincter. Hemorrhoids are most frequently identified by painless bright red bleeding, prolapse, annoying grape-like tissue prolapse, itching, or a combination of symptoms. digital rectal examination (DRE) and anoscope are used to diagnose it. Constipation, a low-fiber diet, a high body- mass index (BMI), pregnancy, and a reduced physical activity are among the factors that are typically thought to increase the risk of hemorrhoids. Golighers is the most commonly used hemorrhoid classification scheme It is 4 degrees, which determines the degree of the event. The purpose of this study is to assess knowledge and awareness level of the causes and stages of Hemorrhoids in the public of Saudi Arabia. Method: This cross-sectional study was conducted in the Saudi Arabia between Oct 2022- Dec 2022. The study group included at least 384 aged above 18 years. The outcomes of this study were analyzed using the SPSS program using a pre-tested questionnaire. Results: The study included 1410 participants, 69.9% of them were females and 30.1% were males. 53.7% of participants aged 20- 30 years old. 17% of participants had hemorrhoids and 42% had a relative who had hemorrhoids. 42.8% of participants could identify stage 1 of hemorrhoids correctly, 44.7% identified stage 2 correctly, 46.7% identified stage 3 correctly and 58.1% identified stage 4 correctly. Only 28.9% of participants had high level of knowledge about hemorrhoids, 62.7% had moderate knowledge and 8.4% had low knowledge. Conclusion: In conclusion, Saudi general population has poor knowledge of hemorrhoids, their causes and their management approach. There was a significant association between knowledge scores of hemorrhoids with age, gender, residence area and employment.

Keywords: hemorrhoids, external hemorrhoid, internal hemorrhoid, anal fissure, hemorrhoid stages, prolapse, rectal bleeding

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Authors: Nkereke M. Essien

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The intention of this paper is to examine stress in the Educated Nigerian Accent of English (ENAE) with the aim of analyzing stress and rhythmic patterns of Nigerian English. Our aim also is to isolate differences and similarities in the stress patterns studied and also know what forms the accent of these Educated Nigerian English (ENE) which marks them off from other groups or English’s of the world, to ascertain and characterize it and to provide documented evidence for its existence. Nigerian stress and rhythmic patterns are significantly different from the British English stress and rhythmic patterns consequently, the educated Nigerian English (ENE) features more stressed syllables than the native speakers’ varieties. The excessive stressed of syllables causes a contiguous “Ss” in the rhythmic flow of ENE, and this brings about a “jerky rhythm’ which distorts communication. To ascertain this claim, ten (10) Nigerian speakers who are educated in the English Language were selected by a stratified Random Sampling technique from two Federal Universities in Nigeria. This classification belongs to the education to the educated class or standard variety. Their performance was compared to that of a Briton (control). The Metrical system of analysis was used. The respondents were made to read some words and utterance which was recorded and analyzed perceptually, statistically and acoustically using the one-way Analysis of Variance (ANOVA). The Turky-Kramer Post Hoc test, the Wilcoxon Matched Pairs Signed Ranks test, and the Praat analysis software were used in the analysis. It was revealed from our findings that the Educated Nigerian English speakers feature more stressed syllables in their productions by spending more time in pronouncing stressed syllables and sometimes lesser time in pronouncing the unstressed syllables. Their overall tempo was faster. The ENE speakers used tone to mark prominence while the native speaker used stress to mark pronounce, typified by the control. We concluded that the stress pattern of the ENE speakers was significantly different from the native speaker’s variety represented by the control’s performance.

Keywords: accent, Nigerian English, rhythm, stress

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Authors: Karin M. Granstrom

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Paper mills produce wastewater with a high content of organic substances. Treatment usually consists of sedimentation, biological treatment of activated sludge basins, and chemical precipitation. The resulting sludges are currently a waste problem, deposited in landfills or used as low-grade fuels for incineration. There is a growing awareness of the need for energy efficiency and environmentally sound management of sludge. A resource-efficient method would be to digest the wastewater sludges anaerobically to produce biogas, refine the biogas to biomethane for use in the transportation sector, and utilize the resulting digestate for soil improvement. The biomethane yield of pulp and paper wastewater sludge is comparable to that of straw or manure. As a bonus, the digestate has an improved dewaterability compared to the feedstock biosludge. Limitations of this process are predominantly a weak economic viability - necessitating both sufficiently large-scale paper production for the necessary large amounts of produced wastewater sludge, and the resolving of remaining questions on the certifiability of the digestate and thus its sales price. A way to improve the practical and economical feasibility of using paper mill wastewater for biomethane production and soil improvement is to co-digest it with other feedstocks. In this study, pulp and paper sludge were co-digested with (1) silage and manure, (2) municipal sewage sludge, (3) food waste, or (4) microalgae. Biomethane yield analysis was performed in 500 ml batch reactors, using an Automatic Methane Potential Test System at thermophilic temperature, with a 20 days test duration. The results show that (1) the harvesting season of grass silage and manure collection was an important factor for methane production, with spring feedstocks producing much more than autumn feedstock, and pulp mill sludge benefitting the most from co-digestion; (2) pulp and paper mill sludge is a suitable co-substrate to add when a high nitrogen content cause impaired biogas production due to ammonia inhibition; (3) the combination of food waste and paper sludge gave higher methane yield than either of the substrates digested separately; (4) pure microalgae gave the highest methane yield. In conclusion, although pulp and paper mills are an almost untapped resource for biomethane production, their wastewater is a suitable feedstock for such a process. Furthermore, through co-digestion, the pulp and paper mill wastewater and mill sludges can aid biogas production from more nutrient-rich waste streams from other industries. Such co-digestion also enhances the soil improvement properties of the residue digestate.

Keywords: anaerobic, biogas, biomethane, paper, sludge, soil

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Authors: Constantine Uwaremwe, Wenjie Bao, Bachir Goudia Daoura, Sandhya Mishra, Xianxian Zhang, Lingjie Shen, Shangwen Xia, Xiaodong Yang

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Background: Plukenetia volubilis Linneo is an oleaginous plant belonging to the family Euphorbiaceae. Due to its seeds containing a high content of edible oil and rich in vitamins, P. volubilis is cultivated as an economical plant worldwide. However, the cultivation and growth of P. volubilis is challenged by phytopathogen invasion leading to production loss. Methods: In the current study, we tested the pathogenicity of fungal pathogens isolated from root rot infected P. volubilis plant tissues by inoculating them into healthy P. volubilis seedlings. Metagenomic sequencing was used to assess the shift in the fungal community of P. volubilis rhizosphere soil after root rot infection. Results: Four Fusarium isolates and two Rhizopus isolates were found to be root rot causative agents of P. volubilis as they induced typical root rot symptoms in healthy seedlings. The metagenomic sequencing data showed that root rot infection altered the rhizosphere fungal community. In root rot infected soil, the richness and diversity indices increased or decreased depending on pathogens. The four most abundant phyla across all samples were Ascomycota, Glomeromycota, Basidiomycota, and Mortierellomycota. In infected soil, the relative abundance of each phylum increased or decreased depending on the pathogen and functional taxonomic classification. Conclusions: Based on our results, we concluded that Fusarium and Rhizopus species cause root rot infection of P. volubilis. In root rot infected P. volubilis, the shift in the rhizosphere fungal community was pathogen-dependent. These findings may serve as a key point for a future study on the biocontrol of root rot of P. volubilis.

Keywords: fusarium spp., plukenetia volubilis l., rhizopus spp., rhizosphere fungal community, root rot

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Authors: Sapan Bhatnagar

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Micron size particles emitted from different sources and produced by combustion have serious negative effects on human health and environment. They can penetrate deep into our lungs through the respiratory system. Determination of the amount of particulates present in the atmosphere per cubic meter is necessary to monitor, regulate and model atmospheric particulate levels. Cascade impactor is used to collect the atmospheric particulates and by gravimetric analysis, their concentration in the atmosphere of different size ranges can be determined. Cascade impactors have been used for the classification of particles by aerodynamic size. They operate on the principle of inertial impaction. It consists of a number of stages each having an impaction plate and a nozzle. Collection plates are connected in series with smaller and smaller cutoff diameter. Air stream passes through the nozzle and the plates. Particles in the stream having large enough inertia impact upon the plate and smaller particles pass onto the next stage. By designing each successive stage with higher air stream velocity in the nozzle, smaller diameter particles will be collected at each stage. Particles too small to be impacted on the last collection plate will be collected on a backup filter. Impactor consists of 4 stages each made of steel, having its cut-off diameters less than 10 microns. Each stage is having collection plates, soaked with oil to prevent bounce and allows the impactor to function at high mass concentrations. Even after the plate is coated with particles, the incoming particle will still have a wet surface which significantly reduces particle bounce. The particles that are too small to be impacted on the last collection plate are then collected on a backup filter (microglass fiber filter), fibers provide larger surface area to which particles may adhere and voids in filter media aid in reducing particle re-entrainment.

Keywords: aerodynamic diameter, cascade, environment, particulates, re-entrainment

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

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Authors: Thinakar Mani Balusamy, Ratnakar S. Kini, Bharat Narasimhan, Venkateswaran A. R, Pugazhendi Thangavelu, Mohammed Ali, Prem Kumar K., Kani Sheikh M., Sibi Thooran Karmegam, Radhakrishnan N., Mohammed Noufal

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Introduction: Pancreatic injury remains a complicated condition requiring an individualized case by case approach to management. In this study, we aim to analyze the varied presentations and treatment outcomes of traumatic pancreatic injury in a tertiary care center. Methods: All consecutive patients hospitalized at our center with traumatic pancreatic injury between 2013 and 2017 were included. The American Association for Surgery of Trauma (AAST) classification was used to stratify patients into five grades of severity. Outcome parameters were then analyzed based on the treatment modality employed. Results: Of the 35 patients analyzed, 26 had an underlying blunt trauma with the remaining nine presenting due to penetrating injury. Overall in-hospital mortality was 28%. 19 of these patients underwent exploratory laparotomy with the remaining 16 managed nonoperatively. Nine patients had a severe injury ( > grade 3) – of which four underwent endotherapy, three had stents placed and one underwent an endoscopic pseudocyst drainage. Among those managed nonoperatively, three underwent a radiological drainage procedure. Conclusion: Mortality rates were clearly higher in patients managed operatively. This is likely a result of significantly higher degrees of major associated non-pancreatic injuries and not just a reflection of surgical morbidity. Despite this, surgical management remains the mainstay of therapy, especially in higher grades of pancreatic injury. However we would like to emphasize that endoscopic intervention definitely remains the preferred treatment modality when the clinical setting permits. This is especially applicable in cases of main pancreatic duct injury with ascites as well as pseudocysts.

Keywords: endotherapy, non-operative management, surgery, traumatic pancreatic injury

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Authors: Akintunde Alo

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The incessant encroachments into the forest ecosystem by the farmers and local contractors constitute a major threat to the conservation of genetic resources and biodiversity in Nigeria. To propose a viable monitoring system, this study employed Geographic Information System (GIS) technology to assess the changes that occurred for a period of five years (between 2011 and 2016) in Ikere forest reserve. Landsat imagery of the forest reserve was obtained. For the purpose of geo-referencing the acquired satellite imagery, ground-truth coordinates of some benchmark places within the forest reserve was relied on. Supervised classification algorithm, image processing, vectorization and map production were realized using ArcGIS. Various land use systems within the forest ecosystem were digitized into polygons of different types and colours for 2011 and 2016, roads were represented with lines of different thickness and colours. Of the six land-use delineated, the grassland increased from 26.50 % in 2011 to 45.53% in 2016 of the total land area with a percentage change of 71.81 %. Plantations of Gmelina arborea and Tectona grandis on the other hand reduced from 62.16 % in 2011 to 27.41% in 2016. The farmland and degraded land recorded percentage change of about 176.80 % and 8.70 % respectively from 2011 to 2016. Overall, the rate of deforestation in the study area is on the increase and becoming severe. About 72.59% of the total land area has been converted to non-forestry uses while the remnant 27.41% is occupied by plantations of Gmelina arborea and Tectona grandis. Interestingly, over 55 % of the plantation area in 2011 has changed to grassland, or converted to farmland and degraded land in 2016. The rate of change over time was about 9.79 % annually. Based on the results, rapid actions to prevail on the encroachers to stop deforestation and encouraged re-afforestation in the study area are recommended.

Keywords: land use change, forest reserve, satellite imagery, geographical information system

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Authors: Hortènsia Curell, Ana Fernández-Montraveta

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This paper presents the creation, development, and analysis of a corpus designed to study the presence of attitude markers and author’s stance in research articles in two different areas of linguistics (theoretical linguistics and sociolinguistics). These two disciplines are expected to behave differently in this respect, given the disparity in their discursive conventions. Attitude markers in this work are understood as the linguistic elements (adjectives, nouns and verbs) used to convey the writer's stance towards the content presented in the article, and are crucial in understanding writer-reader interaction and the writer's position. These attitude markers are divided into three broad classes: assessment, significance, and emotion. In addition to them, we also consider first-person singular and plural pronouns and possessives, modal verbs, and passive constructions, which are other linguistic elements expressing the author’s stance. The corpus, Corpus of Attitude in Academic Writing (CAAW), comprises a collection of 21 articles, collected from six journals indexed in JCR. These articles were originally written in English by a single native-speaker author from the UK or USA and were published between 2022 and 2023. The total number of words in the corpus is approximately 222,400, with 106,422 from theoretical linguistics (Lingua, Linguistic Inquiry and Journal of Linguistics) and 116,022 from sociolinguistics journals (International Journal of the Sociology of Language, Language in Society and Journal of Sociolinguistics). Together with the corpus, we present the tool created for the creation and storage of the corpus, along with a tool for automatic annotation. The steps followed in the compilation of the corpus are as follows. First, the articles were selected according to the parameters explained above. Second, they were downloaded and converted to txt format. Finally, examples, direct quotes, section titles and references were eliminated, since they do not involve the author’s stance. The resulting texts were the input for the annotation of the linguistic features related to stance. As for the annotation, two articles (one from each subdiscipline) were annotated manually by the two researchers. An existing list was used as a baseline, and other attitude markers were identified, together with the other elements mentioned above. Once a consensus was reached, the rest of articles were annotated automatically using the tool created for this purpose. The annotated corpus will serve as a resource for scholars working in discourse analysis (both in linguistics and communication) and related fields, since it offers new insights into the expression of attitude. The tools created for the compilation and annotation of the corpus will be useful to study author’s attitude and stance in articles from any academic discipline: new data can be uploaded and the list of markers can be enlarged. Finally, the tool can be expanded to other languages, which will allow cross-linguistic studies of author’s stance.

Keywords: academic writing, attitude, corpus, english

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Authors: O. Onoriode Emoyan, E. Eyitemi Akporhonor, Charles Otobrise

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Polycyclic Aromatic Hydrocarbons (PAHs) are formed mainly as a result of incomplete combustion of organic materials during industrial, domestic activities or natural occurrence. Their toxicity and contamination of terrestrial and aquatic ecosystem have been established. Though with limited validity index, previous research has focused on PAHs isomer pair ratios of variable physicochemical properties in source identification. The objective of this investigation was to determine the empirical validity of Pearson correlation coefficient (PCC) and cluster analysis (CA) in PAHs source identification along soil samples of different land uses. Therefore, 16 PAHs grouped as endocrine disruption substances (EDSs) were determined in 10 sample stations in top and sub soils seasonally. PAHs was determined the use of Varian 300 gas chromatograph interfaced with flame ionization detector. Instruments and reagents used are of standard and chromatographic grades respectively. PCC and CA results showed that the classification of PAHs along kinetically and thermodyanamically-favoured and those derived directly from plants product through biologically mediated processes used in source signature is about the predominance PAHs are likely to be. Therefore the observed PAHs in the studied stations have trace quantities of the vast majority of the sixteen un-substituted PAHs which may ultimately inhabit the actual source signature authentication. Type and extent of bacterial metabolism, transformation products/substrates, and environmental factors such as: salinity, pH, oxygen concentration, nutrients, light intensity, temperature, co-substrates and environmental medium are hereby recommended as factors to be considered when evaluating possible sources of PAHs.

Keywords: comparative correlation, kinetically and thermodynamically-favored PAHs, pearson correlation coefficient, cluster analysis, sources evaluation

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: Dana Alina Magdas, Nicoleta Simona Vedeanu, Ioana Feher, Rares Stiufiuc

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Food and beverages authentication using rapid and non-expensive analytical tools represents nowadays an important challenge. In this regard, the potential of vibrational techniques in food authentication has gained an increased attention during the last years. For wines discrimination, Raman spectroscopy appears more feasible to be used as compared with IR (infrared) spectroscopy, because of the relatively weak water bending mode in the vibrational spectroscopy fingerprint range. Despite this, the use of Raman technique in wine discrimination is in an early stage. Taking this into consideration, the wine discrimination potential of surface-enhanced Raman scattering (SERS) technique is reported in the present work. The novelty of this study, compared with the previously reported studies, concerning the application of vibrational techniques in wine discrimination consists in the fact that the present work presents the wines differentiation based on the individual signals obtained from deconvoluted spectra. In order to achieve wines classification with respect to variety, geographical origin and vintage, the peaks intensities obtained after spectra deconvolution were compared using supervised chemometric methods like Linear Discriminant Analysis (LDA). For this purpose, a set of 20 white Romanian wines from different viticultural Romanian regions four varieties, was considered. Chemometric methods applied directly to row SERS experimental spectra proved their efficiency, but discrimination markers identification found to be very difficult due to the overlapped signals as well as for the band shifts. By using this approach, a better general view related to the differences that appear among the wines in terms of compositional differentiation could be reached.

Keywords: chemometry, SERS, variety, wines discrimination

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: lexicon of disasters, modelling, Petri nets, text annotation, social disasters

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Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

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The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

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Authors: Amin Naboureh, Ainong Li, Jinhu Bian, Guangbin Lei, Hamid Ebrahimy

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Large-scale land cover mapping has become a new challenge in land change and remote sensing field because of involving a big volume of data. Moreover, selecting the right classification method, especially when there are different types of landscapes in the study area is quite difficult. This paper is an attempt to compare the performance of different machine learning (ML) algorithms for generating a land cover map of the China-Central Asia–West Asia Corridor that is considered as one of the main parts of the Belt and Road Initiative project (BRI). The cloud-based Google Earth Engine (GEE) platform was used for generating a land cover map for the study area from Landsat-8 images (2017) by applying three frequently used ML algorithms including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). The selected ML algorithms (RF, SVM, and ANN) were trained and tested using reference data obtained from MODIS yearly land cover product and very high-resolution satellite images. The finding of the study illustrated that among three frequently used ML algorithms, RF with 91% overall accuracy had the best result in producing a land cover map for the China-Central Asia–West Asia Corridor whereas ANN showed the worst result with 85% overall accuracy. The great performance of the GEE in applying different ML algorithms and handling huge volume of remotely sensed data in the present study showed that it could also help the researchers to generate reliable long-term land cover change maps. The finding of this research has great importance for decision-makers and BRI’s authorities in strategic land use planning.

Keywords: land cover, google earth engine, machine learning, remote sensing

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Authors: Tadele Tesfaw, Ajit Pal Singh, Abebaw Mekonnen Gezahegn

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Welding is a basic manufacturing process for making components or assemblies. Recent welding economics research has focused on developing the reliable machinery database to ensure optimum production. Research on welding of materials like steel is still critical and ongoing. Welding input parameters play a very significant role in determining the quality of a weld joint. The metal active gas (MAG) welding parameters are the most important factors affecting the quality, productivity and cost of welding in many industrial operations. The aim of this study is to investigate the optimization process parameters for metal active gas welding for 60x60x5mm dead mild steel plate work-piece using Taguchi method to formulate the statistical experimental design using semi-automatic welding machine. An experimental study was conducted at Bishoftu Automotive Industry, Bishoftu, Ethiopia. This study presents the influence of four welding parameters (control factors) like welding voltage (volt), welding current (ampere), wire speed (m/min.), and gas (CO2) flow rate (lit./min.) with three different levels for variability in the welding hardness. The objective functions have been chosen in relation to parameters of MAG welding i.e., welding hardness in final products. Nine experimental runs based on an L9 orthogonal array Taguchi method were performed. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the welding characteristics of dead mild steel plate and used in order to obtain optimum levels for every input parameter at 95% confidence level. The optimal parameters setting was found is welding voltage at 22 volts, welding current at 125 ampere, wire speed at 2.15 m/min and gas flow rate at 19 l/min by using the Taguchi experimental design method within the constraints of the production process. Finally, six conformations welding have been carried out to compare the existing values; the predicated values with the experimental values confirm its effectiveness in the analysis of welding hardness (quality) in final products. It is found that welding current has a major influence on the quality of welded joints. Experimental result for optimum setting gave a better hardness of welding condition than initial setting. This study is valuable for different material and thickness variation of welding plate for Ethiopian industries.

Keywords: Weld quality, metal active gas welding, dead mild steel plate, orthogonal array, analysis of variance, Taguchi method

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Authors: Shu-Ching Chen, Li-Yun Lee

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The purpose of the study was to identify the factors associated with head and neck cancer-related lymphoedema (HNCRL)-related symptoms, body image, and HNCRL-related functional outcomes among patients with resected advanced head and neck cancer. A cross-sectional correlational design was conducted to examine the predictors of HNCRL-related functional outcomes in patients with resected advanced head and neck cancer. Eligible patients were recruited from a single medical center in northern Taiwan. Consecutive patients were approached and recruited from the Radiation Head and Neck Outpatient Department of this medical center. Eligible subjects were assessed for the Symptom Distress Scale–Modified for Head and Neck Cancer (SDS-mhnc), Brief International Classification of Functioning, Disability and Health (ICF) Core Set for Head and Neck Cancer (BCSQ-H&N), Body Image Scale–Modified (BIS-m), The MD Anderson Head and Neck Lymphedema Rating Scale (MDAHNLRS), The Foldi’s Stages of Lymphedema (Foldi’s Scale), Patterson’s Scale, UCLA Shoulder Rating Scale (UCLA SRS), and Karnofsky’s Performance Status Index (KPS). The results showed that the worst problems with body HNCRL functional outcomes. Patients’ HNCRL symptom distress and performance status are robust predictors across over for overall HNCRL functional outcomes, problems with body HNCRL functional outcomes, and activity and social functioning HNCRL functional outcomes. Based on the results of this period research program, we will develop a Cancer Rehabilitation and Lymphedema Care Program (CRLCP) to use in the care of patients with resected advanced head and neck cancer.

Keywords: head and neck cancer, resected, lymphedema, symptom, body image, functional outcome

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Authors: Munmunlisa Mohanty, K. D. Raju

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Rail industry is one of the model employers in India has separate national legislation (Railways Act 1989) to regulate its vast employment structure, functioning across the country. Indian Railway is not only the premier transport industry of the country; indeed, it is Asia’s most extensive rail network organisation and the world’s second-largest industry functioning under one management. With the growth of globalization of industrial products, the scope of anti-employment discrimination is no more confined to gender aspect only; instead, it extended to the unregularized classification of labour force applicable in the various industrial establishments in India. And the Indian Rail Industry inadvertently enhanced such discriminatory employment trends by engaging contractual labour in an unprecedented manner. The engagement of contractual labour by rail industry vanished the core “Employer-Employee” relationship between rail management and contractual labour who employed through the contractor. This employment trend reduces the cost of production and supervision, discourages the contractual labour from forming unions, and reduces its collective bargaining capacity. So, the primary intention of this paper is to highlight the increasing discriminatory employment scope for contractual labour engaged by Indian Railways. This paper critically analyses the diminishing perspective of anti-employment opportunity practiced by Indian Railways towards contractual labour and demands an urgent outlook on the probable scope of anti-employment discrimination against contractual labour engaged by Indian Railways. The researcher used doctrinal methodology where primary materials (Railways Act, Contract Labour Act and Occupational, health and Safety Code, 2020) and secondary data (CAG Report 2018, Railways Employment Regulation Rules, ILO Report etc.) are used for the paper.

Keywords: anti-employment, CAG Report, contractual labour, discrimination, Indian Railway, principal employer

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Authors: Fatemeh Parhizkar, Mojtaba Yamani, Abdolla Behboodi, Masoomeh Hashemi

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The mangrove forests are natural and valuable gifts that exist in some parts of the world, including Iran. Regarding the threats faced by these forests and the declining area of them all over the world, as well as in Iran, it is very necessary to manage and monitor them. The current study aimed to investigate the changes in mangrove forests and the relationship between these changes and the marine hydrodynamics and coastal morphology in the area between qeshm island and the west coast of the Hormozgan province (i.e. the coastline between Mehran river and Bandar-e Pol port) in the 49-year period. After preprocessing and classifying satellite images using the SVM, MLC, and ANN classifiers and evaluating the accuracy of the maps, the SVM approach with the highest accuracy (the Kappa coefficient of 0.97 and overall accuracy of 98) was selected for preparing the classification map of all images. The results indicate that from 1972 to 1987, the area of these forests have had experienced a declining trend, and in the next years, their expansion was initiated. These forests include the mangrove forests of Khurkhuran wetland, Muriz Deraz Estuary, Haft Baram Estuary, the mangrove forest in the south of the Laft Port, and the mangrove forests between the Tabl Pier, Maleki Village, and Gevarzin Village. The marine hydrodynamic and geomorphological characteristics of the region, such as average intertidal zone, sediment data, the freshwater inlet of Mehran river, wave stability and calmness, topography and slope, as well as mangrove conservation projects make the further expansion of mangrove forests in this area possible. By providing significant and up-to-date information on the development and decline of mangrove forests in different parts of the coast, this study can significantly contribute to taking measures for the conservation and restoration of mangrove forests.

Keywords: mangrove forests, marine hydrodynamics, coastal morphology, west of strait of Hormuz, Iran

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Authors: Hasan Frookh Jamal

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This is a case of a 36-year-old Bahraini gentleman diagnosed to have Cushing's Syndrome with a large anterior mediastinal mass. He was sent abroad to the Speciality hospital in Jordan, where he underwent diagnostic video-assisted thoracoscopy, partial thymectomy and pericardial fat excision. Histopathology of the mass was reported to be an Atypical carcinoid tumor with a low Ki67 proliferation index of 5%, the mitotic activity of 4 MF/10HPF and pathological stage classification(pTNM): pT1aN1. MRI of the pituitary gland showed an ill-defined non-enhancing focus of about 3mm on the Rt side of the pituitary on coronal images, with a similar but smaller one on the left side, which could be due to enhancing pattern rather than a real lesion as reported. The patient underwent Ga68 Dotate PET/CT scan post-operatively, which showed multiple somatostatin receptor-positive lesions seen within the tail, body and head of the pancreas and positive somatostatin receptor lymph nodes located between the pancreatic head and IVC. There was no uptake detected at the anterior mediastinum nor at the site of thymic mass resection. There was no evidence of any positive somatostatin uptake at the soft tissue or lymph nodes. The patient underwent IPSS, which proved that the source is, in fact, an ectopic source of ACTH secretion. Unfortunately, the patient's serum cortisol remained elevated after surgery and failed to be suppressed by 1 mg ODST and by 2 days LLDST with a high ACTH value. The patient was started on Osilodrostat for treatment of hypercortisolism for the time being and his future treatment plan with Lutetium-177 Dotate therapy vs. bilateral adrenalectomy is to be considered in an MDT meeting.

Keywords: cushing syndrome, neuroendocrine tumur, carcinoid tumor, Thymoma

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Authors: Chiyoung Kim, Jaegeol Yim

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Bus service is often either main or the only public transportation available in cities. In metropolitan areas, both subways and buses are available whereas in the medium sized cities buses are usually the only type of public transportation available. Bus Information Systems (BIS) provide current locations of running buses, efficient routes to travel from one place to another, points of interests around a given bus stop, a series of bus stops consisting of a given bus route, and so on to users. Thanks to BIS, people do not have to waste time at a bus stop waiting for a bus because BIS provides exact information on bus arrival times at a given bus stop. Therefore, BIS does a lot to promote the use of buses contributing to pollution reduction and saving natural resources. BIS implementation costs a huge amount of budget as it requires a lot of special equipment such as road side equipment, automatic vehicle identification and location systems, trunked radio systems, and so on. Consequently, medium and small sized cities with a low budget cannot afford to install BIS even though people in these cities need BIS service more desperately than people in metropolitan areas. It is possible to provide BIS service at virtually no cost under the assumption that everybody carries a smartphone and there is at least one person with a smartphone in a running bus who is willing to reveal his/her location details while he/she is sitting in a bus. This assumption is usually true in the real world. The smartphone penetration rate is greater than 100% in the developed countries and there is no reason for a bus driver to refuse to reveal his/her location details while driving. We have developed a mobile app that periodically reads values of sensors including GPS and sends GPS data to the server when the bus stops or when the elapsed time from the last send attempt is greater than a threshold. This app detects the bus stop state by investigating the sensor values. The server that receives GPS data from this app has also been developed. Under the assumption that the current locations of all running buses collected by the mobile app are recorded in a database, we have also developed a web site that provides all kinds of information that most BISs provide to users through the Internet. The development environment is: OS: Windows 7 64bit, IDE: Eclipse Luna 4.4.1, Spring IDE 3.7.0, Database: MySQL 5.1.7, Web Server: Apache Tomcat 7.0, Programming Language: Java 1.7.0_79. Given a start and a destination bus stop, it finds a shortest path from the start to the destination using the Dijkstra algorithm. Then, it finds a convenient route considering number of transits. For the user interface, we use the Google map. Template classes that are used by the Controller, DAO, Service and Utils classes include BUS, BusStop, BusListInfo, BusStopOrder, RouteResult, WalkingDist, Location, and so on. We are now integrating the mobile app system and the web app system.

Keywords: bus information system, GPS, mobile app, web site

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Authors: Chun-Min Lin, Yuh-Jen Wu, Ching-Ting Chung

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The formulation of tourism policies requires objective academic research and evidence as support, especially research from local academia. Taiwan is a small island, and its economic growth relies heavily on tourism revenue. Taiwanese government has been devoting to the promotion of the tourism industry over the past few decades. Scientific research outcomes by Taiwanese scholars may and will help lay the foundations for drafting future tourism policy by the government. In this study, a total of 120 full journal articles published between 2008 and 2016 from the Journal of Tourism and Leisure Studies (JTSL) were examined to explore the scientific research trend of tourism study in Taiwan. JTSL is one of the most important Taiwanese journals in the tourism discipline which focuses on tourism-related issues and uses traditional Chinese as the study language. The method of co-word analysis from bibliometrics approaches was employed for semantic analysis in this study. When analyzing Chinese words and phrases, word segmentation analysis is a crucial step. It must be carried out initially and precisely in order to obtain meaningful word or word chunks for further frequency calculation. A word segmentation system basing on N-gram algorithm was developed in this study to conduct semantic analysis, and 100 groups of meaningful phrases with the highest recurrent rates were located. Subsequently, co-word analysis was employed for semantic classification. The results showed that the themes of tourism research in Taiwan in recent years cover the scope of tourism education, environmental protection, hotel management, information technology, and senior tourism. The results can give insight on the related issues and serve as a reference for tourism-related policy making and follow-up research.

Keywords: bibliometrics, co-word analysis, word segmentation, tourism research, policy

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Authors: Shubham Arora

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This paper illustrates a relationship between the Dvaitādvaita (dualistic non-dualistic) doctrine of Nimbārka school of Vedānta and philosophy of Indian classical dance, through the Rasa theory. There would be a separate focus on the philosophies of both the disciplines and then analyzing Rasa theory as a connexion between them. The paper presents ideas regarding the similarity between the Brahman and the dancer, manifestation of enacting character and the Jīva (soul), the existence of the phenomenal world and the imaginary world classification of rasa on the basis of three modes of nature, and the feelings and expressions depicting the Dvaita and Advaita. The reason behind choosing such a topic is an intention to explore the relativity of the Vedantic philosophy of this school in real manner. It is really important to study the practical implications and relevance of the doctrine with other disciplines for perceiving it cogently. In our daily lives, we use various forms of facial expressions and bodily gestures in order to communicate, along with the oral and written means of communication. What if, when gestures and expressions mingle with the music beats, in order to present an idea? Indian Classical dance is highly rich in expressing the emotions using extraordinary expressions, unconventional bodily gestures and mesmerizing music beats. Ancient scriptures like Nāṭyaśāstra of Bharata Muni and Abhinava Bhārati by Abhinavaguptā recount aesthetics in a well-defined and structured way of acting and dancing and also reveal the grammar of rasa theory. Indian Classical dance is not only for entertainment but it is deeply in contact with divinity. During the period of Bhakti movement in India, this art form was used as a means to narrate the vignettes from epics like Rāmāyana and Mahābhārata and Purānas. Even in present era, this art has a deep rooted philosophy within.

Keywords: Advaita, Brahman, Dvaita, Jiva, Nimbarka, Rasa, Vedanta

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Authors: Maimuna Akram, Khadija Zia, Sohaib Naseer

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Pedagogical objectives and the nature of the course content may lead instructors to take varied approaches to selecting a student for the cold call, specifically in a studio setup where students work on different projects independently and show progress work time to time at scheduled critiques. Cold-calling often proves to be an effective tool in eliciting a response without enforcing judgment onto the recipients. While there is a mixed range of behavior exhibited by students who are cold-called, a classification of responses from anxiety-provoking to inspiring may be elicited; there is a need for a greater understanding of utilizing the exchanges in bringing about fruitful and engaging outcomes of studio discussions. This study aims to unravel the dimensions of utilizing the cold-call approach in a didactic exchange within studio pedagogy. A questionnaire survey was conducted in an undergraduate class at Arts and Design School. The impact of cold calling on students’ participation was determined through various parameters, including course choice, participation frequency, students’ comfortability, and teaching methodology. After analyzing the surveys, specific classroom teachers were interviewed to provide a qualitative perspective of the faculty. It was concluded that cold-calling increases students’ participation frequency and also increases preparation for class. Around 67% of students responded that teaching methods play an important role in learning activities and students’ participation during class discussions. 84% of participants agreed that cold calling is an effective way of learning. According to research, cold-calling can be done in large numbers without making students uncomfortable. As a result, the findings of this study support the use of this instructional method to encourage more students to participate in class discussions.

Keywords: active learning, class discussion, class participation, cold calling, pedagogical methods, student engagement

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