Current humanistic design of urban public spaces focuses on specific design elements while ignoring the conflicts and couplings between multiple user needs. This leads to spatial strategies stuck in local optima and lacking overall balance and adaptability. This paper constructs a multi-objective optimization model that integrates user preferences, multidimensional spatial indicators, and behavioral simulation. This model collects field data such as heat maps, path trajectories, and dwell time, identifies user types through K-means clustering, and models their spatial preferences using fuzzy membership functions. Design variables are set in Grasshopper; an optimization function is constructed; the optimal solution is searched using NSGA-III. Finally, pedestrian simulation is performed in AnyLogic, and the optimization results are corrected for function deviation to improve the coordination and adaptability of the design. Experimental results show that this strategy framework significantly improves spatial coordination, increasing weighted average satisfaction from 0.61 to 0.81 (+32.8%), reducing safety risks by 30.8% to 63.2%, and increasing interaction promotion by 71.2%. Multi-dimensional indicators verify the effectiveness of the optimization strategy in balancing user needs, alleviating local conflicts, and enhancing spatial adaptability, providing a quantitative basis and practical path for systematically solving the local optimal problem of humanized design of public spaces.
Ivana Valentina Lemmuela, Mewati Ayub, Oscar Karnalim
Background: Communication is important for everyone, including individuals with hearing and speech impairments. For this demographic, sign language is widely used as the primary medium of communication with others who share similar conditions or with hearing individuals who understand sign language. However, communication difficulties arise when individuals with these impairments attempt to interact with those who do not understand sign language.
Objective: This research aims to develop models capable of recognizing sign language movements in Bahasa and converting the detected gesture into corresponding words, with a focus on vocabularies related to religious activities. Specifically, the research examined dynamic sign language in Bahasa, which comprised gestures requiring motion for proper demonstration.
Methods: In accordance with the research objective, sign language recognition model was developed using MediaPipe-assisted extraction process. Recognition of dynamic sign language in Bahasa was achieved through the application of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) methods.
Results: Sign language recognition model developed using bidirectional LSTM showed the best result with a testing accuracy of 100%. However, the best result for the CNN alone was 86.67 %. The integration of CNN and LSTM was observed to improve performance than CNN alone, with the best CNN-LSTM model achieving an accuracy of 95.24%.
Conclusion: The bidirectional LSTM model outperformed the unidirectional LSTM by capturing richer temporal information, with a specific consideration of both past and future time steps. Based on the observations made, CNN alone could not match the effectiveness of the Bidirectional LSTM, but a combination of CNN with LSTM produced better results. It is also important to state that normalized landmark data was found to significantly improve accuracy. Accuracy within this context was also influenced by shot type variability and specific landmark coordinates. Furthermore, the dataset containing straight-shot videos with x and y coordinates provided more accurate results, dissimilar to those comprised of videos with shot variation, which typically require x, y, and z coordinates for optimal accuracy.
Keywords: Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), MediaPipe, Sign Language
The development of society is accompanied by an increase in the complexity of management objects and management mechanisms. To counteract the growth of complexity, new management models and methods should be introduced. New methods include semasiological management which uses a model approach and induction principle. It borrows the ideas of semasiology from linguistics and forms management decisions on the basis of application of information management units. Despite the fact that this complicates the preliminary process of preparing for management, it also gives an advantage in the comparability of different management decisions and technologies. Semasiological management allows, when reconfiguring management, not to create management models anew, but to modernise them by replacing management information units or forming new combinations of these units. Semasiological management is related to onomasiological information modeling and requires its use. In addition, it can be used in automated management, smart management, and digital twin management. Semasiological management requires special organisation and specific training, such as a special management language. The research proposes a variant of semasiological management which is based on the application of the theory of information units.
Josenaide Alves da Silva, Geilsa Costa Santos Baptista, Nataélia Alves da Silva
A pesquisa é qualitativa e o objetivo propõe a análise da comunicação dos licenciandos para desenvolvimento de um ensino intercultural em aulas de ciências. Os envolvidos no trabalho foram dois licenciandos do curso de Ciências Agrárias, do Instituto Federal de Educação, Ciências e Tecnologia Baiano, do campus de Senhor do Bonfim-BA. Para coleta de dados, utilizou-se gravações em vídeos, procedendo a Análise de Conteúdo e a Estrutura de análise das classes comunicativas, para analisá-los. Este artigo apresenta resultados sobre as análises das aulas de ciências dos licenciandos, as quais direcionaram para o desenvolvimento da abordagem comunicativa dialógica, incluindo os saberes socioculturais dos estudantes e os saberes científicos, a partir de uma relação entre essas formas de conhecer. Considera-se que a abordagem comunicativa dialógica é um alicerce para os licenciandos ministrarem a prática de ciências contextualizada.
Special aspects of education, Applied mathematics. Quantitative methods
Three levels, namely the device level, the connection level, and the systems management level, are frequently used to conceptualize intelligent machinery and Industry 4 [...]
Navaneethakrishna Makaram, Sarvagya Gupta, Matthew Pesce
et al.
In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images is an alternative to signal inspection, but subtle variations may escape the human eye. Here, we propose a deep learning-based metric of visual complexity to interpret TF images extracted from iEEG data and aim to assess its ability to identify the EZ in the brain. We analyzed interictal iEEG data from 1928 contacts recorded from 20 children with drug-resistant epilepsy who became seizure-free after neurosurgery. We localized each iEEG contact in the MRI, created TF images (1–70 Hz) for each contact, and used a pre-trained VGG16 network to measure their visual complexity by extracting unsupervised activation energy (UAE) from 13 convolutional layers. We identified points of interest in the brain using the UAE values via patient- and layer-specific thresholds (based on extreme value distribution) and using a support vector machine classifier. Results show that contacts inside the seizure onset zone exhibit lower UAE than outside, with larger differences in deep layers (L10, L12, and L13: <i>p</i> < 0.001). Furthermore, the points of interest identified using the support vector machine, localized the EZ with 7 mm accuracy. In conclusion, we presented a pre-surgical computerized tool that facilitates the EZ localization in the patient’s MRI without requiring long-term iEEG inspection.
Robert Mroczyński, Grzegorz Głuszko, Romuald B. Beck
et al.
This work reports on changes in the properties of ultra-thin PECVD silicon oxynitride layers after high- temperature treatment. Possible changes in the structure, composition and electrophysical properties were investigated by means of spectroscopic ellipsometry, XPS, SIMS and electrical characterization methods (C-V, I-V and charge- pumping). The XPS measurements show that SiOxNy is the dominant phase in the ultra-thin layer and high-temperature annealing results in further increase of the oxynitride phase up to 70% of the whole layer. Despite comparable thickness, SIMS measurement indicates a densification of the annealed layer, because sputtering time is increased. It suggests complex changes of physical and chemical properties of the investigated layers taking place during high-temperature annealing. The C-V curves of annealed layers exhibit less frequency dispersion, their leakage and charge-pumping currents are lower when compared to those of as-deposited layers, proving improvement in the gate structure trapping properties due to the annealing process.
Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici
et al.
<b>Background</b>: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurately distinguish CSF from neural or other tissues based on the center voxel and neighboring voxels. <b>Methods</b>: 88 regions of interest (ROIs) from 12 patients’ dual-energy (100 and 140 kVp) lumbar spine CT exams were manually labeled by a neuroradiologist as one of 4 major tissue types (water, fat, bone, and nonspecific soft tissue). Four-class classifier convolutional neural networks were trained, validated, and tested on thousands of nonoverlapping patches extracted from 82 ROIs among 11 CT exams, with each patch representing pixel values (at low and high energies) of small, rectangular, 3D CT volumes. Different patch sizes were evaluated, ranging from 3 × 3 × 3 × 2 to 7 × 7 × 7 × 2. A final ensemble model incorporating all patch sizes was tested on patches extracted from six ROIs in a holdout patient. <b>Results</b>: Individual models showed overall test accuracies ranging from 99.8% for 3 × 3 × 3 × 2 patches (N = 19,423) to 98.1% for 7 × 7 × 7 × 2 patches (N = 1298). The final ensemble model showed 99.4% test classification accuracy, with sensitivities and specificities of 90% and 99.6%, respectively, for the water class and 98.6% and 100% for the soft tissue class. <b>Conclusions</b>: Convolutional neural networks utilizing local low-level features on dual-energy spine CT can yield accurate tissue classification and enhance the visualization of intraspinal neural tissue.
With the increasing demand of individual customption and awareness of cost reduction in express delivery organizations, the Chinese express industry faced with serious challenges especially under the background of government’s strict restrictions on environment and transportation. Therefore, a new service mode called joint distruction (JD) is being tried by the logistics industry, which is expected to address the challenges on online shopping. However, the insufficient understanding of JD adoption factors and their complicated interactions blocks the effectively implementation of the joint distribution. This study aims at identifying potential factors for JD adoption and promoting an effective joint distribution by discovering the interactive relationships among addressed factors. Firstly, potential ingredients for the adoption and implementation of JD are summarized from the literature and industrial interviews. Then, 23 variables are selected and classified into as objectives, drivers, barriers and affected operations. The Interpretive Structural Modeling (ISM) approach is then employed to analyze the crucial factors and the mutual influences amongst 23 variables. Finally, a case study is performed to construct the hierarchical structure of factors toward joint distribution adoption using the proposed ISM-modeling steps. The perplex hierarchical co-relationships are also identified by categorizing the driving variables and dependent variables. Results can assist express enterprises to promote the novel joint distribution mode and acheive higher efficiency of logistics operation by better understanding on crucial factors of JD adoption and implementation.
History of scholarship and learning. The humanities, Social Sciences
This study measured the time it took to select a target moving along a circular trajectory with a computer mouse. The time was changed according to the speed of the target, the width of target and the distance from the starting point to the target. However, the effect of these independent variables on the dependent variable was different from what was expected. In the previous studies, it was assumed that the faster the moving target speed, the longer the target selection time, because increased target speed had the effect of narrowing the effective target width. However, as a result of the experiment, the target selection time was rather shortened when the moving speed of the target was increased. This may be because the subjects intend to speed up target selection while decreasing the accuracy of target selection in order to adapt to a fast-moving target. The modified Fitts’ model for the moving target selection time proposed in a previous study did not take these user responses into account. A more modified model is required to more accurately describe the selection time of moving target.
Edward Bormashenko, Irina Legchenkova, Mark Frenkel
et al.
In this paper, informational (Shannon) measures of symmetry are introduced and analyzed for patterns built of 1D and 2D shapes. The informational measure of symmetry <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>s</mi><mi>y</mi><mi>m</mi></mrow></msub><mrow><mo>(</mo><mi>G</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula> characterizes the averaged uncertainty in the presence of symmetry elements from group <i>G</i> in a given pattern, whereas the Shannon-like measure of symmetry <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi mathvariant="sans-serif">Ω</mi><mrow><mi>s</mi><mi>y</mi><mi>m</mi></mrow></msub><mrow><mo>(</mo><mi>G</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula> quantifies the averaged uncertainty of the appearance of shapes possessing a total of <i>n</i> elements of symmetry belonging to group <i>G</i> in a given pattern. <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>s</mi><mi>y</mi><mi>m</mi></mrow></msub><mrow><mo>(</mo><mrow><msub><mi>G</mi><mn>1</mn></msub></mrow><mo>)</mo></mrow><mo>=</mo><msub><mi mathvariant="sans-serif">Ω</mi><mrow><mi>s</mi><mi>y</mi><mi>m</mi></mrow></msub><mrow><mo>(</mo><mrow><msub><mi>G</mi><mn>1</mn></msub></mrow><mo>)</mo></mrow><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula> for the patterns built of irregular, non-symmetric shapes, where <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>G</mi><mn>1</mn></msub></mrow></semantics></math></inline-formula> is the identity element of the symmetry group. Both informational measures of symmetry are intensive parameters of the pattern and do not depend on the number of shapes, their size, and the entire area of the pattern. They are also insensitive to the long-range order (translational symmetry) inherent for the pattern. Additionally, informational measures of symmetry of fractal patterns are addressed, the mixed patterns including curves and shapes are considered, the time evolution of Shannon measures of symmetry are examined, the close-packed and dispersed 2D patterns are analyzed, and an application of the suggested measures of symmetry for the analysis of the chemical reaction is demonstrated.
During magnetic pulsed welding (MPW), a wavy interface pattern can be observed. However, this depends on the specific material combination being joined. Some combinations, e.g., steel to aluminum, simply provide undulating waves, while others, e.g., titanium to copper, provide elegant vortices. These physical features can affect the strength of the joint produced, and thus a more comprehensive understanding of the material combination effects during MPW is required. To investigate the interfacial morphology and parent material properties dependency during MPW, tubular Al1100 and various copper alloy joints were fabricated. The influence of two material properties, i.e., yield strength and density, were studied, and the interface morphology features were visually investigated. Results showed that both material properties affected the interface morphology. Explicitly, decreasing yield strength (Cu101 and Cu110) led to a wavy interface, and decreasing density (Cu110 and CP-Ti) resulted in a wave interface with a larger wavelength. Numerical analyses were also conducted in LS-DYNA and validated the interface morphologies observed experimentally. These simulations show that the effect on shear stresses in the material is the cause of the interface morphology variations obtained. The results from this research provide a better fundamental understanding of MPW phenomena with respect to the effect of material properties and thus how to design an effective MPW application.
Disseminating information through the World Wide Web as the most popular medium has resulted in creating a huge number of web pages and so growing the dimension of the web. In this era of big data, an efficient website ranking to satisfy the web user requirements in different areas such as marketing and E-commerce is a major challenge in the current Internet. In this context, the role of ranking algorithms as a tool to provide services such as measuring the website visibility and comparing the website position to the competitors is crucial. In this paper, we propose an architecture for web domain ranking which includes processing capability required for handling Big Data available on the web. The proposed architecture presents a new method for web domain ranking that is independent of the link structure of the web graph. The proposed method provides web domain ranking based on the number of unique visitors, the number of user sessions, and session duration.
Eko Wahyu Tyas Darmaningrat, Hanim Maria Astuti, Andhika Iman Rizqy
Revolusi industri 4.0 dan persaingan bisnis yang semakin ketat menjadikan TI sebagai pendukung dalam pencapaian tujuan bisnis utama sebuah perusahaan. Salah satu bentuk dukungan TI dalam organisasi adalah penggunaan perangkat lunak Enterprise Resource Planning (ERP) dalam pengelolaan sumber daya perusahaan. Akan tetapi, dalam banyak kasus implementasi SAP tidak selalu membawa dampak sesuai dengan ekspektasi perusahaan. Hal ini disebabkan SAP menggunakan best practice yang belum tentu memiliki tingkat kesesuaian dengan proses bisnis perusahaan. Sehingga terdapat kesenjangan (gap) antara proses bisnis perusahaan yang digunakan sebagai acuan best practice oleh SAP dan perusahaan yang akan mengimplementasikan sistem ERP. Penelitian ini bertujuan untuk menyusun dokumen pemodelan proses bisnis as-is dan to-be serta mengidentifikasi kesenjangan antara proses bisnis yang sedang berjalan saat ini dengan proses bisnis pada best practice SAP khususnya pada modul Human Capital Management, salah satu modul utama SAP yang memainkan peran penting dalam membangun manajemen sumber daya yang baik di perusahaan. Hasil analisis kesenjangan memperlihatkan perubahan apa saja yang terjadi pada komponen proses bisnis, baik dari sisi aktivitas, sumber daya yang terlibat, kebutuhan kebijakan, dan struktur organisasi. Perubahan yang terjadi karena penerapan SAP sebagai sistem informasi SDM tentunya membawa dampak. Dampak yang diperoleh dari penerapan teknologi biasa disebut dengan nilai (value). Nilai tersebut berupa manfaat yang mengacu kepada peningkatan efisiensi proses kerja yang diterapkan dalam organisasi.
Abstract
Industrial revolution 4.0 and increasingly fierce business competition make IT as main supporter in achieving the main business objectives of an enterprise. One form of IT support within organizations is the use of Enterprise Resource Planning (ERP) software in enterprise resource management. However, the result of many SAP implementation cases do not always in line with the company expectations. This is because SAP used best practices that do not have the same level of compatibility with the company's business processes. Hence, there is a gap between the company's business processes used as the best practice reference by SAP and the company that will implement the ERP system. This study aims to establish as-is and to-be business process modeling documents and identify the gaps between current business processes of the organization and business processes in SAP best practices especially in the Human Capital Management module, one of SAP's main modules that plays an important role in building good resource management in the company. The gap analysis results show what changes occur in the business processes components in terms of activity, the resources involved, policy requirements, and organizational structure. These changes certainly would have some impacts. The impacts is usually called as value. This value is in the form of benefits that refer to an increase in the efficiency of work processes applied in the organization
Persaingan di dalam dunia pendidikan dewasa ini semakin ketat, khususnya perguruan tinggi,
bukan hanya perguruan tinggi dalam negeri saja yang menjadi pesaing tetapi juga perguruan tinggi luar
negeri.Minat masyarakat Indonesia semakin tinggi terhadap perguruan tinggi luar negeri yang
menawarkan kualitas jasa pendidikan yang lebih baik. Adapun tujuan dalam penelitian ini yaitu
Mengukur tingkat kepuasan mahasiswa/i Fakultas Teknik Universitas X terhadap pelayanan jasa yang
diberikan oleh Fakultas Teknik Universitas X. Jenis penelitian yang digunakan adalah penelitian
deskriptif dengan teknik survey.Metode yang digunakan adalah metode Servqual.Metode servqual
digunakan untuk menentukan atribut serta mengukur kesenjangan (gap) antara harapan dengan persepsi
konsumen terhadap suatu pelayanan. Hasil penelitian diperoleh gap Dengan nilai terbesar yakni -0.9186
menunjukkan bahwa fasilitas yang diberikan belum sesuai dengan biaya uang kuliah yang dibayarkan
oleh mahasiswa sedangkan Tingkat pendidikan Dosen yang mengajar di UMA sudah berpendidikan
minimal S2 dengan gap yang bernilai positif sebesar 0.0679 yang mengindekasikan bahwa tingkat
harapan yang ada pada mahasiswa lebih rendah dari kinerja yang diberikan oleh Universitas X.
Industrial engineering. Management engineering, Industry
Maria Alfonsa Chintia Dea Prananingrum, Wellia Shinta Sari
<p><strong><em>Abstrak</em></strong><strong> </strong></p> <p><em>SMA PL Don Bosko Semarang belum dapat memanfaatkan teknologi komputer secara optimal karena masih menggunakan cara manual dalam pengelolaan berbagai macam data akademik sehingga memberikan masalah seperti lambatnya dalam pembuatan laporan yang menyulitkan kepala sekolah dalam pengambilan keputusan. Oleh sebab itu, SMA PL Don Bosko Semarang membutuhkan Sistem Informasi Akademik untuk memberikan kemudahan dalam mengelola berbagai macam data akademik secara terintegrasi serta memberikan layanan yang lebih baik kepada siswanya. Sebuah model architecture enterprise Sistem Informasi Akademik dibutuhkan agar meminimalisir kegagalan ketika menerapkan sistem tersebut sekaligus dapat berjalan sesuai kebutuhan di SMA PL Don Bosko Semarang. Metode analisis dalam penelitian ini menggunakan Framework Zachman yang memberikan pondasi dalam membantu menyediakan struktur dasar organisasi sehingga dapat mendukung perancangan dan pengembangan sistem informasi suatu organisasi. Hasil dari penelitian ini berupa blueprint (cetak biru) pemodelan Sistem Informasi Akademik.</em></p> <p><em> </em></p> <p><strong><em>Kata kunci</em></strong>—<em> </em>sistem informasi akademik, architecture enterprise, framework zachman, bluprint</p> <p><strong> </strong></p>
Performance Management System (PMS) is developed and implemented in organizations to achieve organizational goals effectively. PMS is vital for an organization. In this paper, the association between PMS and Organizational Effectiveness (OE) is explored. The study reveals that there is an association between PMS and OE. The finding is also in line with the previous research studies emphasizing the impact of PMS on OE. The relationship and impact of the variables are justified by the respective statistical values. It establishes the dependence of organizational outcomes on PMS.
Production management. Operations management, Business
The purpose of this article was to evaluate the environmental performance of a medium-sized company that provides services for surface treatment of aluminum. The treatment is known as anodizing. The research method was qualitative numerical modeling. The environmental performance of the company was organized into five constructs: atmosphere, wastewater, energy and natural resources, solid waste, and legislation and management. Nineteen indicators were chosen to explain the five constructs. Ten employees of the company prioritized the constructs and evaluated the situation of the indicators by means of a scale of assessment. By means of a mathematical model, the general performance of the environmental operation was calculated at 74.5% of the maximum possible. The indicators that most contributed to the performance not to reach 100% were consumption of electricity and water consumption. The construct of worse performance was natural and energy resources. These are the priorities for future environmental improvement actions that the company may promote.