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Journal articles on the topic 'Sign of comparison'

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Published: 5 June 2025

Last updated: 15 July 2025

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Dasgupta, S., C. R. Elevitch, G. J. Rey, and C. R. Johnson. "Comparison Between Leaky Sign-sign and LMS Adaptive Algorithms." IFAC Proceedings Volumes 21, no. 9 (1988): 311–14. http://dx.doi.org/10.1016/s1474-6670(17)54744-8.

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Ghari, Zohreh. "Comparative and Superlative Adjectives in Iranian Sign Language." International Journal of Linguistics 14, no. 4 (2022): 141. http://dx.doi.org/10.5296/ijl.v14i4.20166.

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Comparison is an inseparable part of a language. It can be performed using various constructions in both oral and signing languages. English and Persian, for instance use affixes for comparative and superlative adjectives. Sign languages such as Australian Sign Language (Auslan), New Zealand Sign Language (NZSL), American Sign Language (ASL) and British Sign Language (BSL) employ affixes, use intensifiers and nonmanual features (by itself or along with a sign) to indicate a comparison. This research was aimed to investigate the constructions employed to make comparisons in Iranian Sign Language, Zaban Eshare Irani (ZEI). The findings indicate that, besides the aforementioned constructions used in other sign languages, excluding ‘affixes’, the main construction ZEI signers used was descriptive mode of discourse (e.g. Anker 2004), individually explaining the compared topics to clarify their preference. To a lesser extent, numbering, topicalization, and repetition were also used which mostly united together or alone in the same discourse. A similar construction was also observed for both comparative and superlative adjectives. This study opens a new window to comprehend the deaf people’s mind of thinking, and will benefit studies on language and linguistics, sign language interpreters and those that are interested.

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Aldersson, Russell R., and Lisa J. McEntee-Atalianis. "A Lexical Comparison of Signs from Icelandic and Danish Sign Languages." Sign Language Studies 9, no. 1 (2008): 45–87. http://dx.doi.org/10.1353/sls.0.0007.

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Caminschi, Irina, Alexandra J. Corbett, Corina Zahra, et al. "Functional comparison of mouse CIRE/mouse DC-SIGN and human DC-SIGN." International Immunology 18, no. 5 (2006): 741–53. http://dx.doi.org/10.1093/intimm/dxl011.

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Hapuarachchi, Kamal S., and Ian A. Cowan. "The medial breast margin sign: A new sign of pectus excavatum in adult females and comparison with classic signs." Journal of Medical Imaging and Radiation Oncology 63, no. 6 (2019): 737–44. http://dx.doi.org/10.1111/1754-9485.12949.

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McWhorter, John. "Spoken and Sign Language Emergence: A Comparison." Languages 7, no. 3 (2022): 184. http://dx.doi.org/10.3390/languages7030184.

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A comparison of emerging signed languages and creole languages provides evidence that, when language is emerging, it prioritizes marking the novelty of information; is readily recursive; favors the manner of action (aspect) over the time of action (tense); develops inflection readily only in a visual, as opposed to aural, mode; and develops derivational opacity only as the result of drift over long periods of time.

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Oomen, Marloes, and Roland Pfau. "Signing not (or not): A typological perspective on standard negation in Sign Language of the Netherlands." Linguistic Typology 21, no. 1 (2017): 1–51. http://dx.doi.org/10.1515/lingty-2017-0001.

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AbstractThe expression of standard negation by means of manual and/or non-manual markers has been described for a considerable number of sign languages. Typological comparisons have revealed an intriguing dichotomy: while some sign languages require a manual negative element in negative clauses (manual-dominant sign languages), in others negation can be realized by a non-manual marker alone (in particular a headshake; non-manual-dominant sign languages). We are here adding data from Sign Language of the Netherlands (NGT) to the picture, and we demonstrate that NGT belongs to the latter group. Still, detailed comparison suggests that NGT patterns differently from other non-manual-dominant sign languages, thereby improving our understanding of the typological variation in this domain. A novel contribution of the present study is that it is based on naturalistic corpus data, showing more variation than often found in elicitation and grammaticality judgment studies of sign languages, but also presenting new problems of interpretation.

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Fitzpatrick, Kay, Raul Avelar, Tomas Lindheimer, and Marcus A. Brewer. "Comparison of Above-Sign and Below-Sign Placement of Rectangular Rapid-Flashing Beacons." Transportation Research Record: Journal of the Transportation Research Board 2562, no. 1 (2016): 45–52. http://dx.doi.org/10.3141/2562-06.

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Ebling, Sarah, Reiner Konrad, Penny Boyes Braem, and Gabriele Langer. "Factors to Consider When Making Lexical Comparisons of Sign Languages: Notes from an Ongoing Comparison of German Sign Language and Swiss German Sign Language." Sign Language Studies 16, no. 1 (2015): 30–56. http://dx.doi.org/10.1353/sls.2015.0024.

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Sporns, Peter B., Michael Schwake, André Kemmling, et al. "Comparison of Spot Sign, Blend Sign and Black Hole Sign for Outcome Prediction in Patients with Intracerebral Hemorrhage." Journal of Stroke 19, no. 3 (2017): 333–39. http://dx.doi.org/10.5853/jos.2016.02061.

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Bilal, Zaid Saad, Amir Gargouri, Hanaa F. Mahmood, and Hassene Mnif. "Comparison of Collective Diverse Arabic Sign Language Dataset." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 15, no. 4 (2024): 133–50. https://doi.org/10.58346/jowua.2024.i4.009.

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Machine learning researchers from all around the world continue to work out the best ways to collect data efficiently. Data collecting has recently emerged as a key concern for two primary reasons. Despite the fact that machine learning is making significant progress, there may not be enough labelled data for some new applications. Furthermore, deep learning methods have the benefit of automatically creating features, which is not the case with traditional machine learning methods. With this, model design becomes more affordable, although more labelled data may be required. Particularly, the collection of data research has been on the increase in recent years including data management, computer vision, machine learning, and natural language processing. The main reason for this is that it's necessary to handle and process enormous quantities of data successfully. This study primarily aims to present a publicly available dataset comparison that includes large samples of Arabic sign language images for the goal of sign language classification. This dataset collection has a lot of different videos and images that show different moves. The primary objective of this comparison is to show that there are different types of sign language datasets such as words based sign and alphabet based sign furthermore, the comparison include the Background of the Datasets, the Size of the Datasets, the Number of Samples, the Number of Training, Testing, and Validation Samples, the dataset types, and RGB or Binary Images. The main goals of future study will be to improve the method and test the model using AASL-annotated data.

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Wang, Jianwei. "Iconicity in Chinese Sign Language and Filipino Sign Language." English Language Teaching 17, no. 5 (2024): 51. http://dx.doi.org/10.5539/elt.v17n5p51.

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Sign language is primarily used as a means of communication by the deaf and hard of hearing. Iconicity is considered as its typical feature. This paper makes a preliminary comparison on lexical items between Chinese Sign Language (CSL) and Filipino Sign Language (FSL) through examining the iconic devices used by the CSL and FSL signs. The study provides some valuable evidence that the iconicity is prevalent in CSL and FSL which always use similar iconic device for the same concept due to shared embodied experience though different iconic devices are occasionally used. These iconic devices include direct (1) presentation; (2) number representation; (3) shape representation; (4) movement representation (5) size representation; (6) part-for-whole representation; (7) metonymic/metaphorical representation. The findings of the research could help to reveal the relationship between language and cognition and make some contributions to the communications among the deaf and hard of hearing in both Chian and the Philippines.

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Kyuseva, Maria. "Priznakovaya leksika v russkom zhestovom yazyke v tipologicheskoy perspektive [Signs denoting qualities in Russian Sign Language from typological perspective]." Vestnik Moskovskogo Universiteta 3, no. 9 (2017): 97–114. https://doi.org/10.5281/zenodo.10222215.

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The article presents a lexico-semantic analysis of five qualitative fields in Russian Sign Language (RSL: "sharp", "blunt", "old", "thick", "thin") in comparison with spoken languages. The analysis is based on the division of the sign language lexicon into the core and the peripheral signs. The latter are argued to consist of two types of components, namely, specified and non-specified ones. Specified components have a permanent form, while non-specified ones change their form depending on context. This distinction enables an analysis of RSL qualitative fields in the Moscow Lexical Typology Group framework and provides basis for the comparison of these signs with corresponding spoken language words.

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Singh, Rakesh Kumar, Lav Kumar Jaiswal, Tanmayee Nayak, et al. "Expression, Purification, and In Silico Characterization of Mycobacterium smegmatis Alternative Sigma Factor SigB." Disease Markers 2022 (May 20, 2022): 1–11. http://dx.doi.org/10.1155/2022/7475704.

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Sigma factor B (SigB), an alternative sigma factor (ASF), is very similar to primary sigma factor SigA (σ70) but dispensable for growth in both Mycobacterium smegmatis (Msmeg) and Mycobacterium tuberculosis (Mtb). It is involved in general stress responses including heat, oxidative, surface, starvation stress, and macrophage infections. Despite having an extremely short half-life, SigB tends to operate downstream of at least three stress-responsive extra cytoplasmic function (ECF) sigma factors (SigH, SigE, SigL) and SigF involved in multiple signaling pathways. There is very little information available regarding the regulation of SigB sigma factor and its interacting protein partners. Hence, we cloned the SigB gene into pET28a vector and optimized its expression in three different strains of E. coli, viz., (BL21 (DE3), C41 (DE3), and CodonPlus (DE3)). We also optimized several other parameters for the expression of recombinant SigB including IPTG concentration, temperature, and time duration. We achieved the maximum expression of SigB at 25°C in the soluble fraction of the cell which was purified by affinity chromatography using Ni-NTA and further confirmed by Western blotting. Further, structural characterization demonstrates the instability of SigB in comparison to SigA that is carried out using homology modeling and structure function relationship. We have done protein-protein docking of RNA polymerase (RNAP) of Msmeg and SigB. This effort provides a platform for pulldown assay, structural, and other studies with the recombinant protein to deduce the SigB interacting proteins, which might pave the way to study its signaling networks along with its regulation.

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Alalfy, Mahmoud, Seif Ali, Mostafa Ibrahim, et al. "Seif and Alalfy twist sign; a Novel view in fetal echocardiography in evaluation of normal heart." Obstetrics & Gynecology International Journal 16, no. 2 (2025): 47–50. https://doi.org/10.15406/ogij.2025.16.00787.

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Background: Fetal echocardiography is the primary tool for assessment of fetal heart and involves analysis of the cardiac anatomy from many views and Doppler examination of the intracardiac structures, great vessels, and umbilical artery. Patients and methods: A prospective observational comparative study with comparing the Seif and Alalfy twist sign to the standard fetal echocardiography in evaluation of normal heart. Results: Comparison of the Seif and Alalfy twist sign and fetal echocardiography in evaluation of the 4 chamber view revealed same findings. Comparison between Seif and Alalfy twist sign and fetal echocardiography in assessment of outflow tracts revealed the same finding. Conclusion: Seif and Alalfy twist sign is a reliable ultrasound (US) technique in scanning normal heart and could be compared to detailed fetal echocardiography. Sief and Alalfy twist sign as a novel sign in fetal echocardiography as a new, easy, time effective view one step fetal heart examination.

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Gene Hawkins, H., Dale L. Picha, Mark D. Wooldridge, Francis K. Greene, and Greg Brinkmeyer. "Performance Comparison of Three Freeway Guide Sign Alphabets." Transportation Research Record: Journal of the Transportation Research Board 1692, no. 1 (1999): 9–16. http://dx.doi.org/10.3141/1692-02.

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Laudanna, Alessandro, and Virginia Volterra. "Order of words, signs, and gestures: A first comparison." Applied Psycholinguistics 12, no. 2 (1991): 135–50. http://dx.doi.org/10.1017/s0142716400009115.

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ABSTRACTThe present study evaluates the contribution of visuo-gestural modality versus linguistic factors in determining the order of elements in sign language. The same picture description task was given to 12 hearing subjects using spoken Italian, 12 deaf subjects using Italian Sign Language, and 12 hearing subjects using pantomime. Nonreversible, reversible, and locative productions with two elements were elicited. The results showed that Italian Sign Language differs along significant lines from both spoken Italian and pantomime. The pattern of similarities and differences found among the three experimental conditions allows us to argue that the order of signs in the sentence is sensitive to modality as well as linguistic factors depending on the particular sentence structures considered.

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Kumar, Raj, and Ram Awadh Mishra. "Design and analysis of RNS-based sign detector for moduli set {2n , 2n -1, 2n+1}." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 62–70. https://doi.org/10.11591/ijeecs.v22.i1.pp62-70.

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Magnitude comparison, sign detection and overflow detection are essential operations of residue number system (RNS) that are used in digital signal processing (DSP) applications. Moreover, sign detection attracts significant attention in RNS as it can also be used in division and magnitude comparison operations. However, these operations are not easy to perform in RNS. So, there is a need arise to propose a computationally advanced RNS based sign detector. This paper presents an area and power-efficient sign detection circuit for modulo {2n -1, 2n , 2n+1} using mixed radix conversion technique. The proposed sign detector is constructed using a carry save adder (CSA), a modified parallel prefix adder and a carry-generation circuit. Based on the synthesized results using synopsys design compiler, the introduced design offers better results in terms of the area required and power consumption. Although, the speed will remain the same when compared to the recent sign detectors for the same moduli set.

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Mangai .V. "Comparative Analysis of Various Yolo Models for Sign Language Recognition with a specific dataset." Journal of Information Systems Engineering and Management 10, no. 43s (2025): 544–50. https://doi.org/10.52783/jisem.v10i43s.8443.

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Understanding and replaying sign language are the hardcore communication tasks between the normal person and to deaf and dumped person, and vice versa. To enhance sign language-based communication, several models have been developed for making sign language into an understandable format by translating gestures into words. The ultimate goal of this research paper is to analyse and compare the various You Only Look One (YOLO) models on SLR problem. YOLO is a fast and efficient convolutional neural networks (CNN) variant that provides a better solution for sign language problems. The comparison of different YOLO models with Indian Sign Language (ISL) dataset can provide a suitable YOLO model for SLR. Therefore, the proposed work has considered the ISign Benchmark dataset. The ISL-based comparison analysis is implemented on Python tool where the various performance metrics are calculated for selecting the best YOLO model . This will make a way to give a fast and efficient means for recognizing sign gestures.

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Shakya, Milind Ratna, Fan Fu, Miao Zhang, et al. "Comparison of Black Hole Sign, Satellite Sign, and Iodine Sign to Predict Hematoma Expansion in Patients with Spontaneous Intracerebral Hemorrhage." BioMed Research International 2021 (February 1, 2021): 1–8. http://dx.doi.org/10.1155/2021/3919710.

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Purpose. To discretely and collectively compare black hole sign (BHS) and satellite sign (SS) with recently introduced gemstone spectral imaging-based iodine sign (IS) for predicting hematoma expansion (HE) in spontaneous intracerebral hemorrhage (SICH). Methods. This retrospective study includes 90 patients from 2017 to 2019 who underwent both spectral computed tomography angiography (CTA) as well as noncontrast computed tomography (NCCT) within 6 hours of SICH onset along with subsequent follow-up NCCT scanned within 24 hours. We named the presence of any of BHS or SS as any NCCT sign. Two independent reviewers analyzed all the HE predicting signs. Receiver-operator characteristic curve analysis and logistic regression were performed to compare the predictive performance of HE. Results. A total of 61 patients had HE, out of which IS was seen in 78.7% (48/61) while BHS and SS were seen in 47.5% (29/61) and 41% (25/61), respectively. The area under the curve for BHS, SS, and IS was 63.4%, 67%, and 82.4%, respectively, while for any NCCT sign was 71.5%. There was no significant difference between IS and any NCCT sign ( P = 0.108 ). Multivariate analysis showed IS (odds ratio 68.24; 95% CI 11.76-396.00; P < 0.001 ) and any NCCT sign (odds ratio 19.49; 95% CI 3.99-95.25; P < 0.001 ) were independent predictors of HE whereas BHS (odds ratio 0.34; 95% CI 0.01-38.50; P = 0.534 ) and SS (odds ratio 4.54; 95% CI 0.54-38.50; P = 0.165 ) had no significance. Conclusion. The predictive accuracy of any NCCT sign was better than that of sole BHS and SS. Both any NCCT sign and IS were independent predictors of HE. Although IS had higher predictive accuracy, any NCCT sign may still be regarded as a fair predictor of HE when CTA is not available.

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Ramadhan, Muhammad Fajar, Samsuryadi Samsuryadi, and Anggina Primanita. "American Sign Language Translation to Display the Text (Subtitles) using a Convolutional Neural Network." Engineering, MAthematics and Computer Science Journal (EMACS) 6, no. 3 (2024): 163–72. https://doi.org/10.21512/emacsjournal.v6i3.11904.

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Sign language is a harmonious combination of hand gestures, postures, and facial expressions. One of the most used and also the most researched Sign Language is American Sign Language (ASL) because it is easier to implement and also more common to apply on a daily basic. More and more research related to American Sign Language aims to make it easier for the speech impaired to communicate with other normal people. Now, American Sign Language research is starting to refer to the vision of computers so that everyone in the world can easily understand American Sign Language through machine learning. Technology continues to develop sign language translation, especially American Sign Language using the Convolutional Neural Network. This study uses the Densenet201 and DenseNet201 PyTorch architectures to translate American Sign Language, then display the translation into written form on a monitor screen. There are 4 comparisons of data splits, namely 90:10, 80:20, 70:30, and 60:30. The results showed the best results on DenseNet201 PyTorch in the train-test dataset comparison of 70:30 with an accuracy of 0.99732, precision of 0.99737, recall (sensitivity) of 0.99732, specificity of 0.99990, F1-score of 0.99731, and error of 0.00268. The results of the translation of American Sign Language into written form were successfully carried out by performance evaluation using ROUGE-1 and ROUGE-L resulting in a precision of 0.14286, Recall (sensitivity) 0.14286, and F1-score.

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MOMONIAT, E. "A COMPARISON OF DIFFUSION MODELED BY TWO MIXED DERIVATIVE EQUATIONS." Modern Physics Letters B 22, no. 27 (2008): 2709–13. http://dx.doi.org/10.1142/s0217984908017254.

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Fourier and Bessel function solutions of two mixed derivative equations are investigated. For the appropriate sign of the material constants in the derivation of the mixed derivative equation, we obtain both Fourier and Bessel function solutions that tend to the corresponding solutions of the phenomenological diffusion equation. For the opposite sign of the material constants, the solutions diverge.

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Naufal, Mohammad Farid, Sesilia Shania, Jessica Millenia, et al. "Analisis Perbandingan Algoritma Klasifikasi MLP dan CNN pada Dataset American Sign Language." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 3 (2021): 489–95. http://dx.doi.org/10.29207/resti.v5i3.3009.

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People who have hearing loss (deafness) or speech impairment (hearing impairment) usually use sign language to communicate. One of the most basic and flexible sign languages is the Alphabet Sign Language to spell out the words you want to pronounce. Sign language uses hand, finger, and face movements to speak the user's thoughts. However, for alphabetical sign language, facial expressions are not used but only gestures or symbols formed using fingers and hands. In fact, there are still many people who don't understand the meaning of sign language. The use of image classification can help people more easily learn and translate sign language. Image classification accuracy is the main problem in this case. This research conducted a comparison of image classification algorithms, namely Convolutional Neural Network (CNN) and Multilayer Perceptron (MLP) to recognize American Sign Language (ASL) except the letters "J" and "Z" because movement is required for both. This is done to see the effect of the convolution and pooling stages on CNN on the resulting accuracy value and F1 Score in the ASL dataset. Based on the comparison, the use of CNN which begins with Gaussian Low Pass Filtering preprocessing gets the best accuracy of 96.93% and F1 Score 96.97%

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Gusakova, Violetta E., and Svetlana I. Burkova. "Antonymy in Russian sign language." Voprosy Jazykoznanija, no. 1 (August 14, 2024): 60–84. http://dx.doi.org/10.31857/0373-658x.2024.1.60-84.

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The article discusses signs-antonyms in Russian Sign Language from the point of view of how visual modality in which this language exists affects their internal structure. The article shows that the correlation between the structure and semantics of antonymous gestures in Russian Sign Language is built primarily on iconicity and the use of three-dimensional space. This reveals the uniqueness of antonymic relations in sign languages in comparison with those in spoken languages.

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Kumar, Raj, and Ram Awadh Mishra. "Design and analysis of RNS-based sign detector for moduli set {2^n, 2^n - 1, 2^n + 1}." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 62. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp62-70.

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Magnitude comparison, sign detection and overflow detection are essential operations of residue number system (RNS) that are used in digital signal processing (DSP) applications. Moreover, sign detection attracts significant attention in RNS as it can also be used in division and magnitude comparison operations. However, these operations are not easy to perform in RNS. So, there is a need arise to propose a computationally advanced RNS based sign detector. This paper presents an area and power-efficient sign detection circuit for modulo {2n - 1, 2n, 2n + 1} using mixed radix conversion technique. The proposed sign detector is constructed using a carry save adder (CSA), a modified parallel prefix adder and a carry-generation circuit. Based on the synthesized results using synopsys design compiler, the introduced design offers better results in terms of the area required and power consumption. Although, the speed will remain the same when compared to the recent sign detectors for the same moduli set.

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Fatima, Eesham, Waqasia Naeem, and Irfan Abbas. "THE INFLUENCE OF GENDER ON THE DISCOURSE MARKERS IN PAKISTANI SIGN LANGUAGE." Pakistan Journal of Social Research 04, no. 02 (2022): 1201–7. http://dx.doi.org/10.52567/pjsr.v4i2.616.

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This paper aims to shed light on the common discourse markers in Sign Language, particularly Pakistani Sign Language. Pakistani Sign Language is overlooked and emerges as a non-standardized. These gestures/ discourse markers will be studied in comparison to American Sign Language (ASL). The main features will be analysed that call for a detailed analysis based on the use, the universality and application. This research aims to study if there is any influence of gender on these discourse markers. The Pakistan Sign Language Corpus will be collected and analysed with the assistance of Sign Language Interpreters. Furthermore, to see for any consistent language specific functions that these languages may share will also be accounted and noted. Keywords: Sign Language, Discourse markers, gender, American Sign Language, Pakistani Sign Language

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Zivkovic, Dragica, and Jasmina Jovanovic. "Comparison of morphemic word structure and a cartographic sign." Glasnik Srpskog geografskog drustva 91, no. 1 (2011): 159–70. http://dx.doi.org/10.2298/gsgd1101159z.

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Language is a system of gestures, sounds, characters, symbols and words that are used to display concepts and communication. Map language is derived from natural language, rather than parallel to it, as its graphical equivalent. Natural and mapping language is based on a system of signs. In the natural language, the letters are the smallest units, and arranged meaningfully they constitute a sign - a word i.e. a concept. In a cartographic language one sign is one term. But common to both languages is the basis of character - morphemes and its accessories - affixes, which in the cartographic language have greater possibilities of expression.

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Dell'Aversano, A., A. Natale, and R. Solimene. "Comparison between different decorrelation techniques in vital sign detection." Advanced Electromagnetics 5, no. 2 (2016): 53. http://dx.doi.org/10.7716/aem.v5i2.397.

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The problem of detecting the breath activities of a human subject is addressed. A CW signal is used to probe the scene and the MUSIC algorithm is exploited to detect frequency doppler modulation introduced by chest movements. For this particular measurement configuration, the correlation matrix results rank deficient. In order to restore the rank, two decorrelation techniques are compared by exploiting numerical data.

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Ebert, Cornelia. "A comparison of sign language with speech plus gesture." Theoretical Linguistics 44, no. 3-4 (2018): 239–49. http://dx.doi.org/10.1515/tl-2018-0016.

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Donner, Abigail, Matthew Marshall, and Jacqueline Mozrall. "Biomechanical Comparison of American Sign Language Interpretation and Conversation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 57, no. 1 (2013): 384–88. http://dx.doi.org/10.1177/1541931213571083.

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YAVAŞ, HÜSEYİN GÖKHAN, and ERGİN SAĞTAŞ. "Central vein sign: comparison of multiple sclerosis and leukoaraiosis." Turkish Journal of Medical Sciences 52, no. 6 (2022): 1933–42. http://dx.doi.org/10.55730/1300-0144.5541.

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Wu, Huaxiao, Qinhua Wang, Nayan Deep Tiwari, and Dario De Domenico. "Comparison of Dynamic Responses of Parallel-Placed Adjacent High-Rise Buildings under Wind and Earthquake Excitations." Shock and Vibration 2021 (June 24, 2021): 1–14. http://dx.doi.org/10.1155/2021/6644158.

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Two parallel-placed adjacent high-rise buildings are often linked to each other through passive control devices for vibration mitigation purposes. The mitigation efficiency of these control devices mainly depends on the characteristics of relative dynamic responses, namely, opposite-sign and same-sign responses of the two buildings. The present research first identifies an opposite-sign response factor to estimate the time ratio of opposite-sign responses. Subsequently, a structure comprising two adjacent high-rise buildings (with different natural frequency ratios) subjected to both wind and earthquake excitations is analyzed. Wind-induced responses are evaluated based on wind loads obtained from wind tunnel tests, while earthquake responses are determined through a suite of 44 natural ground-motion records. The results indicate that opposite-sign factors of the displacement, velocity, and acceleration responses under wind loads, especially at across-wind direction, are larger than those under earthquake excitations, and opposite-sign response factors under wind loads are insensitive to variation of the natural frequency ratio of the two adjacent buildings compared with those under earthquake excitations. The conclusions of this research may be helpful for wind-resistant and antiseismic design of parallel-placed adjacent high-rise buildings.

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Capraro, Robert M., Mary Margaret Capraro, Z. Ebrar Yetkiner, Serkan Özel, Hae Gyu Kim, and Ali Riza Küçük. "An International Comparison of Grade 6 Students' Understanding of the Equal Sign." Psychological Reports 106, no. 1 (2010): 49–53. http://dx.doi.org/10.2466/pr0.106.1.49-53.

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This study extends the scope of international comparisons examining students' conceptions of the equal sign. Specifically, Korean ( n = 193) and Turkish ( n = 334) Grade 6 students were examined to assess whether their conceptions and responses were similar to prior findings published for Chinese and U.S. students and to hypothesize relationships about problem types and conceptual understanding of the equal sign. About 59.6% of the Korean participants correctly answered all items providing conceptually accurate solutions, as compared to 28.4% of the Turkish sample. Comparison with previous studies in China and the USA indicated that the Chinese sample outperformed those from other nations, followed by Korea, Turkey, and the USA. In large-scale international studies such as Trends in International Mathematics and Science (TIMSS) and the Programme for International Student Assessment (PISA), students from China and Korea have been among the high achievers.

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Nyst, Victoria. "The depiction of size and shape in gestures accompanying object descriptions in Anyi (Côte d’Ivoire) and in Dutch (The Netherlands)." Gesture 15, no. 2 (2016): 156–91. http://dx.doi.org/10.1075/gest.15.2.02nys.

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A comparison of size gestures made during object descriptions by Anyi speakers from the Ivory Coast and Dutch speakers in the Netherlands reveals considerable formational differences. Firstly, whereas all Anyi speakers make use of body parts to depict size and shape, none of the Dutch speakers do. Secondly, Dutch gestures outlining a size and shape in space are more varied than their Anyi counterparts in the number and distribution of the different handshapes, orientations, and movements. In addition, we report comparisons among Anyi speakers in which body parts are used as a way of showing the size of objects with signs for sizes employed in the sign language used by deaf and hearing signers in Adamorobe, a village community in Ghana that is linguistically and culturally related to the Anyi communities in Côte d’Ivoire. This comparison reveals significant similarities as well as differences, suggesting how co-speech gestures may have been adapted for use in this sign language.

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Enns, Charlotte, Vera Kolbe, and Claudia Becker. "Challenges and solutions in test adaption." Sign Language and Linguistics 24, no. 2 (2021): 226–58. http://dx.doi.org/10.1075/sll.20010.enn.

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Abstract Sign language assessment tools are important for professionals working with DHH children to measure sign language development and competence. Adaptation of an existing test can be a solution when initiating assessment in a sign language community; the adaptation process must adhere to key principles and procedures. We introduce the principles of test adaptation and outline the challenges we faced in adapting the British Sign Language Production Test (Herman, Grove, Holmes, Morgan, Sutherland & Woll 2004) to German Sign Language and American Sign Language. Challenges included decisions regarding the normative sample, the use of terminology, and variations in the scoring protocols to fit with each language. The steps taken throughout the test adaptation process are described, together with a comparison of parallels and differences. We conclude that test adaptation is an effective method of developing practical tools for sign language assessment and contributes to a better understanding of sign language development.

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Siddik, A. Muh Amil. "Comparison of Transfer Learning Algorithm Performance in Hand Sign Language Digits Image Classification." Jurnal Matematika, Statistika dan Komputasi 20, no. 1 (2023): 75–89. http://dx.doi.org/10.20956/j.v20i1.26503.

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Image hand sign classification has become an interesting topic in image processing and machine learning. However, to achieve optimal performance in hand sign image classification tasks, a large and diverse dataset as well as powerful learning algorithms are required. One popular technique for improving the performance of classification models is transfer learning, which allows the use of knowledge learned from previous models and applies it to new tasks. In this study, the performance of two different transfer learning algorithms, ResNet-50 and VGG-16, was compared on the Sign Language Digits Dataset, which consists of 10 different types of handwriting images. The results of the experiment showed that both tested transfer learning algorithms had good performance. However, VGG-16 provided the best results with an accuracy of 97,29%, precision of 97,38%, recall of 97,45%, and an F1 score of 97,36%, while ResNet-50 achieved an accuracy of 94,57%, precision of 94,75%, recall of 94,96%, and an F1 score of 94,78%. In conclusion, transfer learning algorithms are effective techniques for improving the performance of hand sign image classification models. Choosing the appropriate transfer learning algorithm and dataset can help generate more accurate classification models.

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Bagaskoro, Muhammad Cahyo, Fadillah Prasojo, Anik Nur Handayani, Emanuel Hitipeuw, Aji Prasetya Wibawa, and Yoeh Wen Liang. "Hand image reading approach method to Indonesian Language Signing System (SIBI) using neural network and multi layer perseptron." Science in Information Technology Letters 4, no. 2 (2023): 97–108. http://dx.doi.org/10.31763/sitech.v4i2.1362.

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Classification complexity is the main challenge in recognizing sign language through the use of computer vision to classify Indonesian Sign Language (SIBI) images automatically. It aims to facilitate communication between deaf or mute and non-deaf individuals, with the potential to increase social inclusion and accessibility for the disabled community. The comparison of algorithm performance in this research is between the neural network algorithm and multi-layer perceptron classification in letter recognition. This research uses two methods, namely a neural network and a multi-layer perceptron, to measure accuracy and precision in letter pattern recognition, which is expected to provide a foundation for the development of better sign language recognition technology in the future. The dataset used consists of 32,850 digital images of SIBI letters converted into alphabetic sign language parameters, which represent active signs. The developed system produces alphabet class labels and probabilities, which can be used as a reference for the development of more sophisticated sign language recognition models. In testing using the neural network method, good discrimination results were obtained with precision, recall and accuracy of around ±81%, while in testing using the multi-layer perceptron method around ±86%, showing the applicative potential of both methods in the context of sign language recognition. Testing of the two normalization methods was carried out four times with comparison of the normalized data, which can provide further insight into the effectiveness and reliability of the normalization technique in improving the performance of sign language recognition systems.

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Wolfe, Rosalee, John C. McDonald, Thomas Hanke, et al. "Sign Language Avatars: A Question of Representation." Information 13, no. 4 (2022): 206. http://dx.doi.org/10.3390/info13040206.

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Given the achievements in automatically translating text from one language to another, one would expect to see similar advancements in translating between signed and spoken languages. However, progress in this effort has lagged in comparison. Typically, machine translation consists of processing text from one language to produce text in another. Because signed languages have no generally-accepted written form, translating spoken to signed language requires the additional step of displaying the language visually as animation through the use of a three-dimensional (3D) virtual human commonly known as an avatar. Researchers have been grappling with this problem for over twenty years, and it is still an open question. With the goal of developing a deeper understanding of the challenges posed by this question, this article gives a summary overview of the unique aspects of signed languages, briefly surveys the technology underlying avatars and performs an in-depth analysis of the features in a textual representation for avatar display. It concludes with a comparison of these features and makes observations about future research directions.

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Sagara, Keiko, and Nick Palfreyman. "Variation in the numeral system of Japanese Sign Language and Taiwan Sign Language." Asia-Pacific Language Variation 6, no. 1 (2020): 119–50. http://dx.doi.org/10.1075/aplv.00009.sag.

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Abstract Abstract (Japanese Sign Language) The numerals 10, 100 and 1,000 are expressed variably in Japanese Sign Language (JSL) and Taiwan Sign Language (TSL), two languages that also have historic links. JSL was used in deaf schools that were established in Taiwan during the Japanese colonial era, leaving a lasting impression on TSL, but complex sociolinguistic situations have led to different outcomes in each case (Fischer, 2014; Sagara, 2014). This comparative sociolinguistic analysis is based on two datasets comprising a total of 1,100 tokens produced by 72 signers from the Kanto and Kansai regions (for JSL) and the cities of Tainan and Taipei (for TSL). Mixed effects modelling reveals that social factors such as the age and region of the signer have a significant influence on how the variable is realised. This investigation shows how careful cross-linguistic comparison can shed light on variation within and between sign languages that have been in contact, and how regional variation in one language may influence regional variation in another.

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Vermeerbergen, Myriam, Mieke Van Herreweghe, Philemon Akach, and Emily Matabane. "Constituent order in Flemish Sign Language (VGT) and South African Sign Language (SASL)." Sign Language and Linguistics 10, no. 1 (2007): 23–54. http://dx.doi.org/10.1075/sll.10.1.04ver.

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This paper reports on a comparison of word order issues, and more specifically on the order of the verb and its arguments, in two unrelated sign languages: South African Sign Language and Flemish Sign Language. The study comprises the first part of a larger project in which a number of grammatical mechanisms and structures are compared across the two sign languages, using a corpus consisting of similar VGT and SASL-data of a various nature. The overall goal of the project is to contribute to a further understanding of the issue of the degree of similarity across unrelated sign languages. However, the different studies also mean a further exploration of the grammars of the two languages involved. In this paper the focus is on the analysis of isolated declarative sentences elicited by means of pictures. The results yield some interesting similarities across all signers but also indicate that — especially with regard to constituent order — there are important differences between the two languages.

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Desser, Terry S., Byard Edwards, Stephen Hunt, Jarrett Rosenberg, Mary Anne Purtill, and R. Brooke Jeffrey. "The dangling diaphragm sign: sensitivity and comparison with existing CT signs of blunt traumatic diaphragmatic rupture." Emergency Radiology 17, no. 1 (2009): 37–44. http://dx.doi.org/10.1007/s10140-009-0819-5.

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Sharma, S., J. Philip, B. Perez, E. Slaymaker, and J. Wiley. "COMPARISON Of 25G PENCAN[registered sign], 2/24G SAFETAP[trade mark sign] And 25G WHITACRE SPINAL NEEDLES." Anesthesia & Analgesia 88, Supplement (1999): 267S. http://dx.doi.org/10.1097/00000539-199902001-00266.

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Rahmawati, Firdha Annisa, Nuram Mubina, and Citra Hati Leometa. "Kepercayaan Diri Perempuan Dewasa Awal: Melihat Pengaruh Citra Tubuh dan Social Comparison Pengguna Instagram di Karawang." Jurnal Psikologi dan Konseling West Science 2, no. 03 (2024): 163–72. http://dx.doi.org/10.58812/jpkws.v2i03.1546.

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Penelitian ini dilaksanakan dalam rangka mengetahui pengaruh citra tubuh dan social comparison terhadap kepercayaan diri perempuan dewasa awal pengguna Instagram di Karawang. Menggunakan metode penelitian secara kuantitatif, dengan desain asosiatif kausalitas. Subjek penelitian ini adalah perempuan berusia 20-40 tahun di Karawang, dengan jumlah responden sebanyak 173 subjek. Instrumen penelitian meliputi skala kepercayaan diri, skala citra tubuh, dan skala social comparison Physical Appearance Comparison Scale-Revised (PACS-R). Analisis data dilakukan dengan uji regresi berganda dengan nilai sign. 0,000 < 0,05 artinya ada pengaruh antara citra tubuh terhadap kepercayaan diri pada perempuan dewasa awal pengguna Instagram di Karawang. Pada social comparison didapati hasil dengan nilai sign. 0,009 < 0,05 artinya ada pengaruh social comparison terhadap kepercayaan diri pada perempuan dewasa awal pengguna Instagram di Karawang. Hasil penelitian diketahui bahwa sumbangsih citra tubuh dan social comparison secara bersama-sama terhadap kepercayaan diri sebesar 25%, sedangkan 75% dipengaruhi oleh faktor lain yang tidak diteliti dalam penelitian ini.

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Watini, Sri, Pipit Nursaputri, and Muhammad Iqbal. "Comparison of CAS and Manage Oauth in Single Sign on (SSO) Client Applications." IAIC Transactions on Sustainable Digital Innovation (ITSDI) 1, no. 2 (2020): 152–59. http://dx.doi.org/10.34306/itsdi.v1i2.147.

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Single Sign On is one of the systems that have been developed long ago to meet the expectations of developers to provide ease and convenience of accessing data. In the development of the system, methods and protocols have been formed in varied ways to suit the needs of the developers . In a variety of methods and protocols , a developer can choose the architecture and protocols that can be used to develop the system. Central Authentication Service and Open authorization is two Single Sign On systems most widely used in the manufacture of a web log . Both can be used as the basis for the application of the system of Single Sign On for developers who intend to design a login system that is safe and comfortable , so that developers can create a system that suits his desire .

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Dachkovsky, Svetlana, Christina Healy, and Wendy Sandler. "Visual intonation in two sign languages." Phonology 30, no. 2 (2013): 211–52. http://dx.doi.org/10.1017/s0952675713000122.

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In a detailed comparison of the intonational systems of two unrelated languages, Israeli Sign Language and American Sign Language, we show certain similarities as well as differences in the distribution of several articulations of different parts of the face and motions of the head. Differences between the two languages are explained on the basis of pragmatic notions related to information structure, such as accessibility and contingency, providing novel evidence that the system is inherently intonational, and only indirectly related to syntax. The study also identifies specific ways in which the physical modality in which language is expressed influences intonational structure.

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Sokipriala, Jonah, and Sunny Orike. "Traffic Sign Classification Comparison Between Various Convolution Neural Network Models." International Journal of Scientific & Engineering Research 12, no. 07 (2021): 165–71. http://dx.doi.org/10.14299/ijser.2021.07.01.

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Fast detection and accurate classiï¬cation of trafï¬c signs is one of the major aspects of advance driver assistance system (ADAS) and intelligent transport systems (ITS), this paper presents a comparison between an 8-Layer convolutional neural network (CNN), and some state of the Arts model such as VGG16 and Resnet50, for trafï¬c sign classiï¬cation on The GTSRB. using a GPU to increase processing time, the design showed that with various augmentation applied to the CNN, our 8-layer Model was able to outperform the State of the Arts models with a higher test Accuracy, 50 times lesser training parameters, and faster training time our 8 -layer model was able to achieve 96% test accuracy.

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Ahlborn, Theresa M., John W. van de Lindt, Alonso J. Uzcategui, and Matthew E. Lewis. "Cost and Performance Comparison of U.S. Overhead Sign Support Structures." Transportation Research Record: Journal of the Transportation Research Board 1892, no. 1 (2004): 14–23. http://dx.doi.org/10.3141/1892-02.

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Napier, Jemina. "Sign Language Interpreter Training, Testing, and Accreditation: An International Comparison." American Annals of the Deaf 149, no. 4 (2004): 350–59. http://dx.doi.org/10.1353/aad.2005.0007.

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Alp, K. Ozlem. "A comparison of sign and symbol (their contents and boundaries)." Semiotica 2010, no. 182 (2010): 1–13. http://dx.doi.org/10.1515/semi.2010.048.

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Brunelli, Michele. "Antisymmetry and sign languages: A comparison between NGT and LIS." New Methodologies in Sign Language Phonology: Papers from TISLR 10 15, no. 1 (2012): 175–83. http://dx.doi.org/10.1075/sll.15.1.09bru.

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