Art Methods Research Articles

3BResNet: COVID19 Tespiti için Yeni Bir Artık Blok Tabanlı ResNet Modeli Yaklaşımı

In recent years, upper respiratory tract infections that have affected the whole world have caused the death of millions of people. It is predicted that similar infections may occur in the coming years. Therefore, it is necessary to develop methods that can be used widely, especially during epidemic periods. The study developed a decision support system for use in upper respiratory tract infections. At this stage, first, the ResNet models in the literature were examined and an application was developed on the SARS-CoV-2 Ct dataset. Next stage, the block structure in the ResNet models in the literature was changed, the number of layers was reduced, and a new model was proposed that provides higher success with fewer parameters. With the proposed model, the values 0.97, 0.97, 0.94, and 0.98 were achieved for accuracy, F1 score, precision and sensitivity on the SARS-CoV-2 Ct dataset, respectively. When the obtained values are compared to state of the art methods in the literature, it has been determined that they are at a competitive level with much fewer parameters. Hardware-related problems encountered in the training of ResNet models at low hardware levels were solved with the proposed model, resulting in a higher success rate. Furthermore, the proposed model can be widely used in different decision support systems that are urgently needed in adverse conditions such as pandemics due to its lightweight structure and high-performance results.

WLP-VBL: A Robust Lightweight Model for Water Level Prediction

Accurate and reliable water level prediction plays a crucial role in the optimal management of water resources and reservoir scheduling. Water level data have the characteristics of volatility and temporality; a single water level prediction model can only be applied to specific hydrological conditions and reservoirs. Therefore, in this paper, we present a robust lightweight model for water level prediction, namely WLP-VBL, by using a combination of VMD, BA, and LSTM. The proposed WLP-VBL model consists of three steps: first, the water level dataset is decomposed by EMD to obtain a number of decomposition layers K, and then VMD is used to decompose the original water level dataset into K intrinsic modal functions (IMFs) to produce a clearer signal. Next, the IMF data are sent to an LSTM neural network optimized by BA for prediction, and finally each component is superimposed to obtain the predicted value. In order to evaluate the effectiveness of the model, experiments were carried out on water level data for the Gan River. The results indicate that: (1) Compared with state-of-the art methods, e.g., LSTM, VMD-LSTM, and EMD-LSTM, WLP-VBL exhibited the best performance. The MSE and MAE of WLP-VBL decreased by 69.6~74.7% and 45~98.5%, respectively. (2) The proposed model showed stronger robustness for water level prediction, and was able to handle highly volatile and noisy data.

Ine, Decorative Art & Design: Current Issues Of The Terminology Correlation.

The aim of the article. To find out the current theoretical and terminological activity caused by the nostrification of artistic and educational processes in Ukraine and the world using educational administration. It is noted that schematics and unification come into conflict with the historically formed terminology in the field of methods of art and design education, which have become the historical image of schools. The global civilizational changes that radically weakened the resistance and ability to self-development of authentic varieties of art are considered. The loss of immunity from unification affected the field of terminology, which is a kind of indicator of changes. The starting position of novelty is the understanding that art is not a resource bound in artificial terminological schemes, but a self-sufficient value. Practical significance. Considering the old and new paradigms, building your system of values is recommended, which are concentrated in the field of terminology. Based on the analysis of a large block of literature, it is recommended to preserve the educational programs "Aesthetics", and "Philosophy of Art" as fundamental in Art Academies of modern Ukraine. The conducted analysis of the literature draws attention to the terminological developments of the Faculty of History and Theory of Art of the Lviv National Academy of Arts, which require systematic continuation. Main results. It has been observed that the obsessive juxtaposition of classical and non-classical vectors of creation, as well as "old and new" terminological systems, psychologically traumatizes artists. Contrasting and unifying involuntarily distorts the truth, and thus harms the art itself. During the periods of Ukraine's statelessness, the enemies politically "justified" the new terms as "relevant" and interpreted the national terms as "obsolete". It is recommended that artists-pedagogues and art historians establish the mission of interpreters and "talismans" of the primary and newest values of fine, applied art and design. The need to correlate artistic and administrative-educational terminology in one's language has been put forward as a major problem. In particular, using the example of fine and decorative arts, it is proposed to use the existing administrative and terminological division of specialties "by default". However, the content-conceptual part of educational programs should be enriched with a historically verified spectrum of terms and concepts with their inherent local connotations. It has been observed that in the historical-artistic and sacral-morphological sense, the term "applied art" is not the same as "craft". The relevance of the commonly used by leading Ukrainian art critics of the 19th and early 20th centuries has been proven of the term "applied": that which is "in life", "in use". It is emphasized that global civilizational changes have radically weakened the resilience and ability to self-develop authentic varieties of applied art. The loss of immunity from administrative unification hurt the field of terminology, which is a kind of indicator of changes

Blood pressure estimation and classification using a reference signal-less photoplethysmography signal: a deep learning framework.

The markers that help to predict th function of a cardiovascular system are hemodynamic parameters like blood pressure (BP), stroke volume, heart rate, and cardiac output. Continuous analysis of hemodynamic parameters such as BP can detect abnormalities earlier, preventing cardiovascular diseases (CVDs). However, sometimes due to motion artifacts, it becomes difficult to monitor the BP accurately and classify it. This work presents an optimized deep learning model having the capability to estimate the systolic blood pressure (SBP) and diastolic blood pressure (DBP) and classify the BP stages simultaneously from the same network using only a single channel photoplethysmography (PPG) signal. The proposed model is designed by exploiting the deep learning framework of a convolutional neural network (CNN), exhibiting the inherent ability to extract features automatically. Moreover, the proposed framework utilizes the superlet transform method to transform a 1-D PPG signal into a 2-D super-resolution time-frequency (TF) spectrogram. A superlet transform separates the peaks related to true PPG signal components and motion artifacts components. Thus, the superlet provides a robust realtime approach to accurately estimating and classifying BP using a single PPG sensor signal and does not require additional ECG and PPG sensor signals for reference. Using a super-resolution spectrogram and CNN model makes the method profitable in motion artifact removal, feature selection, and extraction. Hence the proposed framework becomes less complex for deployment on wearable devices having limited battery resources. The performance of the proposed framework is demonstrated on the publicly available larger dataset MIMIC-III. This work obtained a mean absolute error (MAE) of 2.71mmHg and 2.42mmHg for SBP and DBP, respectively. The classification accuracy for the SBP prediction is about 96.79%, whereas it is 98.94% for DBP. From a motion artifact-affected PPG signal, SBP and DBP are estimated. Then the estimated BP is classified into three categories: normotension, prehypertension, and hypertension, and is compared with the state of art methods to show the effectiveness of the proposed optimized framework.

EEG classification based on Grassmann manifold and matrix recovery

Extracting features from EEG signals through time, frequency and spatial-domain gives rise to the problem of neglecting the property of nonlinear manifold structure of the data, and traditional feature extractions based on Euclidean space are unfavorable for the full utilization of the manifold feature. In this paper, a new EEG classification method is proposed by representing EEG signals on the Grassmann manifold. Firstly, a low rank representation method based on matrix recovery is introduced into the Grassmann manifold to explore the subspace information and re-express the EEG signals. Then a deep neural network is proposed to reduce the dimension of the recovered EEG data, and the low rank representation makes the EEG data separable by using T-SNE visualization; Finally, the dimension reduced features are input to the traditional classifier for classification. The proposed method is performed on four datasets for seizure detection, disease recognition and mental arithmetic recognition respectively. The corresponding accuracy reaches 99.99%, 99.61%, 100%, and 99.72% which shows that the proposed method outperforms other state of art methods on EEG classification.

Fiction and non-fiction in the “thirty-year-old” generation (“millennials”) prose

Based on the analysis of the texts from contemporary Russian literature, the article investigates one of the features of the “thirty-year-old” generation prose (V. Bogdanova, O. Vasyakina, K. Hepting, K. Kupriyanov, E. Manoilo, V. Pustovaya, B. Khanov, I. Khanipaev, et al.). As an additional source, this research uses “thirty-year-old” writers’ interviews and the results of the comparison of their prose with the texts and manifestos of “new realists”. The purpose of the research is to understand the features characterizing the combination of fiction and non-fiction in the latest Russian prose. The article raises the problem of biographical, non-fictional and fictional boundaries in the “thirty-year-old” generation texts. In particular, it appears necessary to understand how the millennial author’s biography is reflected at the levels of the genre, composition and plot. Special attention is paid to the authentic and psychological aspects in the artistic method of “thirty-year-old” writers who include the elements of a diary, confession and Bildungs-roman in the structure and content of their prose. They also create their own pseudo-memories, an alternative history. The research concludes that the “thirty-year-old” generation prose problems and poetics are influenced by the writer’s biography and personality, as well as the specific period of the time they write in.

The aesthetic of structural relationships in linear formations

This research is concerned with the study of (the aesthetic of constructive relations in linear composition) with what distinguished Arabic calligraphy through the style and artistic method in its construction, and the specifications it carries that enabled it to pay attention to building formations to achieve in its total linear ranges aesthetic values and relationships. Through the research, the models and the exploratory study that he obtained, the researcher was able to raise the research problem in the first chapter according to the following question: What is the aesthetic of constructive relations in linear formation?The importance of the research in achieving the aesthetics of the formations, which is a wide field according to the transformation of the structural form, was marked by the search’s disclosure of the aesthetics of the structural relationship in the linear composition written by calligraphers in (Iraq and Turkey) for the period from (1419-1998), (1430-2008) The second chapter included two topics, the first is beauty in Arabic calligraphy, and the second is the aesthetics of constructive relations, and the third chapter includes research procedures based on the descriptive analytical approach. Intentionality was analyzed according to the research tool represented by the research form, which included four pillars whose validity was supervised by a group of specialists.

Grotesque works in children's theater texts

Theater is described as a form of human expression, and an important human necessity, through which the needs of individuals and societies are expressed, and an important mediator for the transfer of educational, social and intellectual dimensions. Hence, the importance of the child’s theater emerged as a guiding educational method that affects the child’s development educationally, emotionally, psychologically and socially through imaginative play that combines enjoyment and entertainment. The grotesque is one of the artistic methods that work to attract the attention of the recipient in theatrical texts that combine dissonance and contradiction in a dramatic act that combines the beautiful and the ugly, the honest and the false together as an expressive method for the theatrical text directed to the child. The first chapter (the methodological framework) dealt with the research problem that was identified in the following axis: What are the works of grotesques in children’s theater texts? The importance of research on the subject of grotesques is evident as it is a sensor that provides researchers and stakeholders in the field of children’s theater by shedding light on the concept of grotesques and its activities in his book the theatrical text directed to the child. Child . The researcher reached the most important results: 1-Presenting what is positive and negative in an objective manner within the drama of the theatrical text 2-The presence of animal and plant characters, which makes the text a kind of humanized plays

Приемы создания портрета главного героя в якутском эпосе (на материале текстов олонхо «Нюргун Боотур Стремительный» П. А. Ойунского и «Строптивый Кулун Куллустуур» И. Г. Тимофеева-Теплоухова)

Introduction. The article examines Yakut heroic olonkho epics — Nyurgun Bootur the Swift by P. Oyunsky and Kulun Kullustuur the Obstinate by I. Timofeev-Teploukhov — for techniques employed to create portraits of main characters. According to N. Yemelyanov, the olonkho Kulun Kullustuur the Obstinate recorded from taleteller I. Timofeev-Teploukhov clusters with earliest patterns of archaic epic, while that of Yakut writer P. Oyunsky (Nyurgun Bootur the Swift) is the first literary adaptation of olonkho texts. The study attempts an insight into how and which particular portrayal techniques were used by P. Oyunsky and I. Timofeev-Teploukhov to depict main characters of theirs. The comparative approach to the narratives recorded in different periods shall make it possible to trace the use of portrayal techniques, which shall underline the unique artistic features characterizing each of the taletellers, and show how such portrayal patterns developed to gain deeper associative essentials in further olonkho texts. Goals. The study aims to identify some distinct features inherent to the techniques of creating main characters’ portraits in the olonkhos Nyurgun Bootur the Swift and Kulun Kullustuur the Obstinate, and outline ethnic specifics in portrayal characteristics. To facilitate this, the paper shall classify portrayals, articulate types of techniques and their functions in portraying a main character, identify stable formulas employed to depict heroes, determine specific features of portrayal as a key technique for the making of an epic hero. The work reviews the existing types of epic portraits, their functions and attributes, examines some visual means serving to unveil the images of main characters. Results. The study attests to the examined narratives are characterized by an increased stability of depictive portrayals with peripheral parts (artistic and emotional epithets) tending to vary. Each such depictive portrayal proves multifunctional, semantically wide, and technically relevant. The descriptions of the heroes’ appearances are somewhat idealized and rich in comparisons, repetitions, evaluative epithets. Portrayal agendas of P. Oyunsky vary through history and depend on actual artistic methods and style employed by the author who pays special attention to fictional details depicted in the context of folk traditions. The study of the techniques helps identify which innovative tools P. Oyunsky used when he was creating his Nyurgun Bootur the Swift.

Stage Unity of D. Lider’s Plastic Concept of Scenography and S. Danchenko’s Theatre Direction

The purpose of the study is to highlight the stage unity of the plastic concept of D. Lider’s scenography and S. Danchenko’s theatre direction, to characterise the original concept of the image of the performances, their uniqueness of artistic solution. The research methodology is to apply the functional and typological method to consider the scenographic activity of D. Lider as an innovative form of artistic creativity in the context of the formation and development of the direction of effective scenography, as well as to assess its significance in the development of scenographic vocabulary of the Ivan Franko National Academic Drama Theatre. The art method is used to analyse the scenographic solution of the performances directed by S. Danchenko and to identify the main conditions and principles of scenographic solutions, compositional techniques and components of D. Lider’s scenography, as well as to determine their influence on the artistic image of the productions. An axiomatic method helped consider Danylo ider's worldview prerogatives in the context of the peculiarities of the formation of his philosophy and artistic and aesthetic position as a master of effective scenography. The novelty of the study. The article comprehensively examines the stage unity of the plastic concept of D. Lider’s scenography and S. Danchenko’s theatre direction in the context of the formation and development of the scenography of the Ivan Franko National Academic Drama Theatre. Conclusions. As a philosopher of theatre, D. Lider’s scenography is not guided by any prescribed rules, and it is impossible to judge it by means of a defining judgment, by imposing certain already known categories on his scenographic vocabulary. The scenery created by the master testifies to an innovative form of the sublime that allows for the acquisition of creative energy – D. Leader sought to overcome the dictates of sensual perception of reality in order to reflect the essential, hidden characteristics of existence. The associative connection and drawing parallels between the actual problems of the present and the problems of a literary work as the basis for deep philosophical and aesthetic reflections introduced by D. Lider is the basis of Ukrainian stage art of the twenty-first century.
 Key words: Danylo Lider, Serhii Danchenko, director, theatre, scenography.

BCAF-3D: Bilateral Content Awareness Fusion for cross-modal 3D object detection

As two major data modalities in autonomous driving, LiDAR point clouds and RGB images include rich geometric clues and semantic features. Compared with using a single data modality, fusing two data modalities can provide complementary information for the 3D object detection task. However, some prevalent cross-modal methods (Vora et al., 2020; Huang et al., 2020; Sindagi et al., 2019) cannot effectively obtain favorable information, and only adopt a unilateral fusion mechanism. In this paper, we propose a novel fusion strategy named Bilateral Content Awareness Fusion (BCAF) to address these issues. Specifically, BCAF adopts a two-stream structure consisting of a LiDAR Content Awareness (LCA) branch and an Image Content Awareness (ICA) branch along with a Soft Fusion (SF) module. First, the LCA and ICA are used to enhance instance-relevant clues. Then, with two awareness features given by the LCA and ICA branches, the aggregation features can be generated to choose favorable image features and LiDAR features. Finally, the SF module fuses the bilateral favorable features and outputs the cross-modal feature. Experiments of our method are conducted on the KITTI dataset, including 3D object detection evaluation and bird’s eye view evaluation. Compared with the previous art method, our approach achieves significant improvements. Especially for the metric of mean Average Precision (mAP) on the Car category, our approach obtains 0.5 and 0.62 gains for the tasks of 3D object detection and bird’s eye view, respectively.

Automatic covariance pattern analysis outperforms visual reading of 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in variant progressive supranuclear palsy.

To date, studies on positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS). To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice. This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern. Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample. Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

SkillsLab+ - Digitization of the Otoscopy Station through State of the Art Methods of Augmented Reality

Abstract The paper discusses SkillsLab+, a medical augmented reality application developed to digitize the practical course SkillsLab. This application provides medical students with a digital tool to learn and apply practical hand movements, initial treatment, and diagnostic techniques. The otoscopy station, one of the stations in SkillsLab+, allows students to learn the correct use of otoscope inserts and perform case discrimination. The digitization of this station provides several advantages over traditional teaching methods. The implementation of the application with the Unreal Engine on the Magic Leap One headset is discussed. The application is modular, allowing the addition of new stations with ease. Anatomically correct models and 3D models of diagnostic tools provide the necessary realism and precision for the application. Learning and exam modes have been included in the application to enhance the learning experience. The evaluation of the application was conducted using a questionnaire completed by 79 bachelor and master students from the fields of medical informatics and digital biomedicine and health sciences. On average, 54.25% of students had a positive response to the digital otoscopy station in the SkillsLab+ application, while 22.71% had a negative response. The questionnaire results indicated that the digitization of the otoscopy station through augmented reality in the SkillsLab+ application was well-received by the students. The SkillsLab+ application digitizes the practical course SkillsLab and offers several advantages over traditional teaching methods. It provides students with a digital tool to learn and apply practical hand movements, initial treatment, and diagnostic techniques. The otoscopy station in SkillsLab+ allows students to learn the correct use of otoscope inserts and perform case discrimination. The digitization of this station provides students with a digital tool that can be used anywhere, any number of times. The evaluation of the application using a questionnaire showed that the application was well received by the students.

Probing the micro- and nanoscopic properties of dental materials using infrared spectroscopy: A proof-of-principle study.

The preservation of oral health over a person's lifespan is a key factor for a high quality of life. Sustaining oral health requires high-end dental materials with a plethora of attributes such as durability, non-toxicity and ease of application. The combination of different requirements leads to increasing miniaturization and complexity of the material components such as the composite and adhesives, which makes the precise characterization of the material blend challenging. Here, we demonstrate how modern IR spectroscopy and imaging from the micro- to the nanoscale can provide insights on the chemical composition of the different material sections of a dental filling. We show how the recorded IR-images can be used for a fast and non-destructive porosity determination of the studied adhesive. Furthermore, the nanoscale study allows precise assessment of glass cluster structures and distribution within their characteristic organically modified ceramic (ORMOCER) matrix and an assessment of the interface between the composite and adhesive material. For the study we used a Fourier-Transform-IR (FTIR) microscope and a quantum cascade laser-based IR-microscope (QCL-IR) for the microscale analysis and a scattering-type scanning near-field optical microscopy (s-SNOM) for the nanoscale analysis. The paper ends with an in-depth discussion of the strengths and weaknesses of the different imaging methods to give the reader a clear picture for which scientific question the microscopes are best suited for. STATEMENT OF SIGNIFICANCE: Modern resin-based composites for dental restoration are complex multi-compound materials. In order to improve these high-end materials, it is important to investigate the molecular composition and morphology of the different parts. An emergent method to characterize these materials is infrared spectroscopic imaging, which combines the strength of infrared spectroscopy and an imaging approach known from optical microscopy. In this work, three state of the art methods are compared for investigating a dental filling including FTIR- and quantum cascade laser IR-imaging microscopy for the microscale and scattering-type scanning near-field optical microscopy for the nanoscale.

A Password and Least Significant Bit Substitution Based Steganography Technique for Image Hiding

The proposed work introduces an image steganography technique using text-based password that acts as the symmetric key of encryption and decryption. It contains two components, an encoder, and a decoder. An encoder takes a secret image that needs to be hidden inside another cover image. The Combined image is encrypted with an eight characters’ password. The starting position of the cover image from where the secret image starts to hide depends on the password. Then the (Least Significant Bit) LSB Substitution technique is used to hide the entire secret image inside the cover image. The decoder takes the encrypted image and the password to retrieve the secret image back. The proposed work produces an encrypted image by keeping 99% information of the cover image and 100% information of the secret image, thus it provides lossless retrieval of the secret image. The proposed work includes dynamicity of position in steganography that ensures more security of image data over the network than the existing state of art methods.

Romanticism in Works of Su Manshu and Yu Dafu: National Characteristics

The article examines the literary movement of romanticism as a creative method employed by Su Manshu and Yu Dafu, two Chinese writers of the first half of the 20th century. The novelty of the research lies in the comparative analysis of the works of these two popular literati, whose prose had a significant influence on the formation of modern Chinese literature. It is reported that the interest of Chinese writers in romantic sentiments was fueled by their exposure to European literature through translations into Japanese and Chinese. Both writers referred to themselves as romantics, but their reasons for being drawn to this artistic method were different. Su Manshu was captivated by the new genre features, such as biographies written from the author’s perspective rather than focusing solely on historical figures, which was sanctioned by traditional literature. Yu Dafu was attracted to the romantic artistic style for its ability to employ unconventional expressive means in Chinese literature. At the same time, the romantic compositions of both writers carry markers of national identity. For Su Manshu, this is evident in the portrayal of female characters, while for Yu Dafu, it is manifested in the use of nature imagery to convey the mood of the characters. The article highlights that the development of romanticism in Chinese literature has been insufficiently studied by Russian sinologists and holds prospects for further research.

Radar-Camera Fusion Network for Depth Estimation in Structured Driving Scenes.

Depth estimation is an important part of the perception system in autonomous driving. Current studies often reconstruct dense depth maps from RGB images and sparse depth maps obtained from other sensors. However, existing methods often pay insufficient attention to latent semantic information. Considering the highly structured characteristics of driving scenes, we propose a dual-branch network to predict dense depth maps by fusing radar and RGB images. The driving scene is divided into three parts in the proposed architecture, each predicting a depth map, which is finally merged into one by implementing the fusion strategy in order to make full use of the potential semantic information in the driving scene. In addition, a variant L1 loss function is applied in the training phase, directing the network to focus more on those areas of interest when driving. Our proposed method is evaluated on the nuScenes dataset. Experiments demonstrate its effectiveness in comparison with previous state of the art methods.

The Position of the God Haldi in the Urartian Kingdom in the light of archaeological sources

The Urartians are considered to be one of the indigenous people of ancient Kurdistan and the Zagros regions in the first millennium B.C, the Kingdom of Urartu covered a vast area, from Syrian Kurdistan in the west and the Black sea in the north to Iranian and Armenian Kurdistan in the east and northest to Diyana, Sidakan and Amedi in southern Kurdistan. In this context, the Urartians were able to become the owners of an important civilization and Kingdom to play their role in the region. In this study we will try to present the position of this God in the light of the archaeological material sources that mention the position of this God in the Kingdom of Urartian. It is worth mentioning that in addition to the cuneiform texts that mention the position of this God in the record of the kings of Urartian. The importance of this study is reflected in the artistic remains left behind by the Urartians throughout their reign. The method of this study is an artistic method to analyze and interpret the position of this God and identify these opinions about his position in the light of material and written archaeological sources. The results of this study showed that the Urartian view of the God Haldi was the source of all Goodness, strength and power so throughout the Kingdom of Urartu remained unchanged until 714 B.C, as a result of the Assyrian Campaign destroyed the city and looted the temple and took away the statue of Haldi and his wife Bakbartu to the city of Musasir, as a result of treaty between the Assyrians and the Urartians, all this evidence confirms that Haldi had prominent position and a significant role in the Kingdom of Urartu.

Smart Home Automation-Based Hand Gesture Recognition Using Feature Fusion and Recurrent Neural Network.

Gestures have been used for nonverbal communication for a long time, but human-computer interaction (HCI) via gestures is becoming more common in the modern era. To obtain a greater recognition rate, the traditional interface comprises various devices, such as gloves, physical controllers, and markers. This study provides a new markerless technique for obtaining gestures without the need for any barriers or pricey hardware. In this paper, dynamic gestures are first converted into frames. The noise is removed, and intensity is adjusted for feature extraction. The hand gesture is first detected through the images, and the skeleton is computed through mathematical computations. From the skeleton, the features are extracted; these features include joint color cloud, neural gas, and directional active model. After that, the features are optimized, and a selective feature set is passed through the classifier recurrent neural network (RNN) to obtain the classification results with higher accuracy. The proposed model is experimentally assessed and trained over three datasets: HaGRI, Egogesture, and Jester. The experimental results for the three datasets provided improved results based on classification, and the proposed system achieved an accuracy of 92.57% over HaGRI, 91.86% over Egogesture, and 91.57% over the Jester dataset, respectively. Also, to check the model liability, the proposed method was tested on the WLASL dataset, attaining 90.43% accuracy. This paper also includes a comparison with other-state-of-the art methods to compare our model with the standard methods of recognition. Our model presented a higher accuracy rate with a markerless approach to save money and time for classifying the gestures for better interaction.

CFD Simulation Study for Abrasive Waste Management Using Water Eductors for Abrasive Waterjet Cutting Collector Tanks

The work is mainly aimed at solving technical problems in the field of unconventional fluid-jet processing, a field in which ISIM Timisoara has developed technical and technological expertise. A crucial part of an effective cleanup process is the secure transportation and disposal of sludge-type materials and related clean-up waste in the industry to a designated site and then to waste treatment plants, as ecological regulations continue to evolve. As a result, experts strive to discover the most state of the art and effective methods for storing and cleaning produced waste.The technical solution studied in this paper consists in obtaining an efficient system for the evacuation of the waste water and abrasive mixture, elements generated during abrasive waterjet cutting, in the shortest time, without stopping the technological cutting process.In this sense, a water eductor system is studied, by carrying out a preliminary experimental program, for use in abrasive waterjet installations collector tanks, by CFD simulation process.The operating parameters of eductor-type mixing nozzles and their effect on the liquid abrasive mixture in a tank of an abrasive-water jet cutting system were analysed.