bluuebunny/crossref_metadata_2025 huggingface dataset:
Educational needs and opportunities for adaptation of students with disabilities and persons with health limitations in the tertiary education system
Authors: Iontseva M. V. , Grishaeva S. A. , Ayvazyan M. A.
Published: June 2023

The article is devoted to the definition consideration of the educational needs of persons with health limitations (hereinafter – HL) and disabled persons in the tertiary education system; the aspects in which these needs are expressed. The article highlights the adaptation possibilities of disabled people in the tertiary education system, as well as the specifics of the organization and goals of an educational institution for teaching people with HL. The authors identify the barriers of social relations faced by students with HL, disabled students and their teachers at universities; analyze the degree of involvement of a student with HL in the educational process. The paper pays attention to the main approaches to the organization of educational activities of persons with HL and disabled people, namely: competence-based, project-based and activity-based approaches. The main types of inclusion, identified on the basis of medical indicators, as conditions for organizing the training of students with HL and disabled students are considered. It is determined that the education organization at the university of students with HL allows to adapt educational programs to the special needs of students, depending on the state of health of students with HL and of disabled students.
Relevance of implementation, application and multimedia technologies’ development in tertiary education
Authors: Tatarinova E. A.
Published: June 2023

The article deals with the advantages and prospects of implementing multimedia technologies necessary for the development of the traditional, already familiar model of education and bringing it to a new level of innovation. The introduction of multimedia technology in educational processes is one of the key moments of education informatization. Nowadays multimedia technologies are one of the most dynamically developing and promising areas of information services. The effectiveness of multimedia methods use directly depends on the professional competence of teachers and the ability to teach graduates the necessary profession skills, which meet modern requirements. The use of e-learning methods opens up opportunities for further implementation of new ideas and trends in the development of tertiary education in Russia. The technological process does not stand still and advanced IT technologies have become an integral part of modern education.
State corporations’ creation for more efficient management of public resources
Authors: Bannikov S. A.
Published: June 2023

In order to fulfill the tasks of sustainable state development, the creation of an innovative economy and the achievement of technological independence it is of particular importance to find ways to improve the efficiency of public resource management. Especially this concerns the development of measures to increase the impact of research and development, and the introduction of new technologies. As part of the implementation of this task, a statistical and economic analysis of the introduction effects of advanced production technologies at enterprises, including in the context of various forms of ownership has been carried out in the work. It is established that the best research results and development work are observed in companies with state participation, especially in state corporations. Thus, one of the most effective forms of innovation economy development in Russia is the further creation of state-owned companies in the most high-tech areas.
Simulation of duplicate tooling consumption at aircraft manufacturing enterprises
Authors: Vdovin V. A. , Afanasieva O. A.
Published: June 2023

To simulate the consumption of duplicate technological tooling (hereinafter referred to as TT), it is proposed to use the apparatus of multivariate regression analysis, which provides the main patterns formalization of consumption formation value in the form of linear regression dependencies. An important difference of the proposed approach to the development of regression models is an increased degree of detail due to the use of the number of detail operations performed using specific TT sizes as independent variables, which makes it possible to eliminate the calculation error associated with the presence of passing positions in the planning period (batches of parts and assembly units ). As a result, a quantitative assessment of the constructed dependencies based on the calculation of multiple correlation coefficients, the Fisher dispersion ratio, the Theil’s coefficient of irrelevance allowed us to conclude that they are adequate to the conditions of consumption TT at the aviation enterprise. To improve the adequacy of displaying real processes of TT consumption, the developed models are equipped with a parametric adaptation mechanism. The use of the steepest descent method makes it possible to adjust the regression parameters based on incoming data, taking into account the main trends in the development of the simulated process and providing for smoothing its random fluctuations.
Discrete optimizations’ problems of deliveries of heterogeneous products
Authors: Egorov V. V.
Published: June 2023

The article touches upon issues related to the tasks of the national project «Smart City». The paper analyzes the problem of supplying a conditional consumer with heterogeneous products in accordance with his demand for deliveries from several suppliers in a situation with fixed surcharges, in addition to the cost of purchasing each unit of production. For the situation under study, a model of a reduced transport type with a discontinuous piecewise linear objective function of minimized total costs and with a system of linear constraints is constructed. A method for finding the optimal solution one of the many such solutions, based on the ideas of the Hungarian algorithm is proposed, the justification of which is given on the basis of the corresponding lemma. A refinement of the method is presented in the presence of some restrictions related to suppliers. The polynomial complexity of the method, i.e. the problem is quickly solvable, and the significant limitation of the applicability of the method within the framework of the model are noted. Further possible research directions of a stochastic or fuzzy nature are indicated.
The Catalytic Reaction of Cytochrome c Oxidase Probed by In Situ Gas Titrations and FTIR Difference Spectroscopy
Authors: Baserga Federico , Storm Julian , Schlesinger Ramona , Heberle Joachim , Stripp Sven
Published: June 2023

Cytochrome c oxidase (CcO) is a transmembrane heme-copper metalloenzyme that catalyzes the reduction of O2 to H2O at the reducing end of the respiratory electron transport chain. To understand this reaction, we followed the conversion of CcO from Rhodobacter sphaeroides between several active-ready and carbon monoxide-inhibited states via attenuated total reflection Fourier-transform infrared (ATR FTIR) difference spectroscopy. Utilizing a novel gas titration setup, we prepared the mixed-valence, CO-inhibited R2CO state as well as the fully-reduced R4 and R4CO states and induced the “active ready” oxidized state OH. These experiments are performed in the dark yielding FTIR difference spectra exclusively triggered by exposure to O2, the natural substrate of CcO. Our data demonstrate that the presence of CO at heme a3 does not impair the catalytic oxidation of CcO when the cycle starts from the fully-reduced states. Interestingly, when starting from the R2CO state, the release of the CO ligand upon purging with inert gas yield a product that is indistinguishable from photolysis-induced states. The observed changes at heme a3 in the catalytic binuclear center (BNC) result from the loss of CO and are unrelated to electronic excitation upon illumination. Based on our experiments, we re-evaluate the assignment of marker bands that appear in time-resolved photolysis and perfusion-induced experiments on CcO.
Legacy and Emerging Plasticizers and Stabilizers in PVC Floorings: Impacts of an Industrial Transition and Recycling
Authors: Wiesinger Helene , Bleuler Christophe , Christen Verena , Favreau Philippe , Hellweg Stefanie , Langer Miriam , Pasquettaz Roxane , Schönborn Andreas , Wang Zhanyun
Published: June 2023

Hazardous chemicals in building and construction plastics can lead to significant indoor exposure, health risks, and contamination of recycled materials. We systematically sample new PVC floor-ings on the Swiss market (n=151). We conduct elemental analysis using XRF, targeted and sus-pect GC MS analysis of ortho phthalates and alternative plasticizers, and bioassay tests for cyto-toxicity, oxidative stress, and endocrine, mutagenic, and genotoxic activities (for selected sam-ples). Surprisingly, 16% of the samples contain regulated chemicals above 0.1 weight%, mainly lead and bis(2-ethylhexyl) phthalate (DEHP). Their presence is likely linked with the use of recy-cled PVC in new floorings, highlighting that uncontrolled recycling can delay the phase-out of hazardous chemicals. Furthermore, 29% of the samples contain ortho-phthalates besides DEHP (mainly diisononyl and diisodecyl phthalates, DiNP and DiDP) above 0.1 weight%, and 17% of the 85 tested samples cause certain adverse biological effects. Together, they make up an addi-tional 35% of samples of potential concern. Moreover, both suspect screening and bioassay results indicate the presence of additional (potentially) hazardous substances, including emerging alterna-tive plasticizers. Overall, our study highlights the urgent need for accelerating the phase-out of hazardous substances and enhancing transparency of chemical compositions in plastics to protect human and ecosystem health and enable the transition to a safe and sustainable circular economy.
Finite-size Effects on the Calculation of X-ray Scattering from Molecular Dynamics Simulations
Authors: Ougaard Dohn Asmus , Markmann Verena Isabell , Nimmrich Amke , Haldrup Kristoffer , Møller Klaus Braagaard , Nielsen Martin Meedom
Published: June 2023

Structural studies using x-ray scattering methods for investigating molecules in solution are shifting focus towards describing the role and effects of the surrounding solvent. However, forward models based on molecular dynamics (MD) simulations to simulate structure factors and x-ray scattering from interatomic distributions such as radial distribution functions (RDFs) face limitations imposed by simulations, particularly at low values of the scattering vector q. In this work, we show how the value of the structure factor at q = 0 calculated from RDFs sampled from finite MD simulations is effectively dependent on the size of the simulation cell. To eliminate this error, we derive a new scheme to renormalize the sampled RDFs based on a model of the excluded volume of the particle-pairs they were sampled from, to emulate sampling from an infinite system. We compare this new correction method to two previous RDF- correction methods, developed for Kirkwood-Buff theory applications. We present a quantitative test to assess the reliability of the simulated low-q scattering signal, and show that our RDF-correction successfully recovers the correct q = 0 limit for neat water. We investigate the effect of MD-sampling time on the RDF-corrections, before advancing to a molecular example system, comprised of a transition metal complex solvated in a series of water cells with varying densities. We show that our correction recovers the correct q = 0 behaviour for all densities. Furthermore, we employ a simple continuum scattering model to dissect the total scattering signal from the solvent-solvent structural correlations in a solute-solvent model system to find two distinct contributions: a non-local density-contribution from the finite, fixed cell size in NVT simulations, and a local contribution from the solvent shell. We show how the second contribution can be approximated without also including the finite-size contribution. Finally, we provide a ’best-practices’-checklist for experimentalists planning to incorporate explicit solvation MD simulations in future work, offering guidance for improving the accuracy and reliability of structural studies using x-ray scattering methods in solution.
A Porous Azatruxene Covalent Organic Framework as Positive Electrode Materials in Li- and Mg-based Batteries
Authors: Pallasch Sebastian , Bhosale Manik , Smales Glen J. , Schmidt Caroline , Riedel Sibylle , Zhao-Karger Zhirong , Esser Birgit , Dumele Oliver
Published: June 2023

Covalent-organic frameworks (COFs) containing defined redox-active groups have become competitive materials for next-generation batteries. Although a high rate performance can be anticipated, to date only few examples of p-type COFs have been reported for charge storage, and even fewer examples regarding the use of COFs in multivalent ion batteries exist. We herein report the synthesis of an azatruxene-based COF and its application as positive electrode material in Li- and Mg-based batteries. By solvothermal condensation a highly porous and crystalline COF was obtained, confirmed by N2 adsorption and intense powder X-ray diffraction (PXRD) reflexes. The electron-rich azatruxene monomer shows up to three reversible one-electron oxidations that make it attractive for anion storage. In Li-based cells using a COF/CNT electrode an average discharge potential of 3.9 V is obtained and discharge capacities of up to 70 mAh g−1 at 2 C rate. In Mg batteries using a tetrakis(hexafluoroisopropyloxy) borate electrolyte cycling proceeds with an average discharge voltage of 2.9 V. Even at a fast current rate of 5C, the capacity retention amounts to 84% over 1000 cycles, and the cells deliver an energy density of 112 Wh kg−1.
All-Organic Battery Based on Deep Eutectic Solvent and Redox-Active Polymers
Authors: Uhl Matthias , Sadeeda . , Penert Philipp , Schuster Philipp A. , Schick Benjamin W. , Muench Simon , Farkas Attila , Schubert Ulrich S. , Esser Birgit , Kuehne Alexander J. C. , Jacob Timo
Published: June 2023

Sustainable battery concepts are of great importance for the energy storage demands of the future. Organic batteries based on redox-active polymers are one class of promising storage systems to meet these demands, in particular when combined with environmentally friendly and safe electrolytes. Deep Eutectic Solvents (DESs) represent a class of electrolytes that can be produced from sustainable sources and exhibit in most cases no or only a small environmental impact. Because of their non-flammability, DESs are safe, while providing an electrochemical stability window almost comparable to established battery electrolytes and much broader than typical aqueous electrolytes. Here, we report the first all-organic battery cell based on a DES electrolyte composed of sodium bis(trifluoromethanesulfonyl)imide (NaTFSI) and N-methylacetamide (NMA) alongside the electrode active materials poly(2,2,6,6-tetramethylpiperidin-1-yl-oxyl methacrylate) (PTMA) and crosslinked poly(vinylbenzylviologen) (X-PVBV2+). The resulting cell shows two voltage plateaus at 1.07 V and 1.58 V and achieves Coulombic efficiencies of 98 %. Surprisingly, the X-PVBV/X-PVBV+ redox couple turned out to be much more stable in NaTFSI:NMA 1:6 than the X-PVBV+/X-PVBV2+ couple, leading to asymmetric capacity fading during cycling tests.
The location and composition of Group 3: A follow-on examination
Authors: Vernon Rene
Published: June 2023

This article is a follow-on to the author’s 2021 arguments on the location and composition of Group 3, a topic which continues to attract interest (Cotton 2022; Neve 2022). In three parts I examine the matter via (a) a critique of the provisional report of the IUPAC Group 3 project (Scerri 2021a); (b) a critique of “In praise of triads” by Scerri (2022a); and (c) electron configuration arguments. The provisional report of the IUPAC Group 3 project is found to lack objectivity; the scientific basis of triads and the notion of a fundamental periodic table are challenged; and electron configuration arguments support Group 3 as Sc-Y-La-Ac.
Surface Directed Growth of a Stable Free Radical Polymer Layer
Authors: Quadrelli Alessio , Robson Alexander , Bashayr Alanazi , Almughathawi Renad , Naderi Javad , Ismael Ali , Lambert Colin , Short Rob , Jarvis Samuel
Published: June 2023

Molecular radicals such as nitric oxide (NO) play a role in numerous important biological processes. NO, however, is inherently unstable, and there is considerable interest in stable radicals with analogous behaviour, such as (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO), and their potential as biologically active surface coatings. Here we show that it is possible to grow stable TEMPO monolayers with an ordered arrangement and specific orientation of the nitroxide group. A combination of high-resolution atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations reveal that strong dipole-dipole interactions between neighbouring TEMPO molecules determine their orientation, resulting in an anti-parallel arrangement with upwards and downwards facing nitroxide groups. Surface coating is made possible using plasma polymerisation, a surface molecular engineering technique suitable for growing functional coatings of highly stable organic molecules. Typically, plasma polymerisation is considered a surface-independent process, with the plasma power and pressure dominating the deposited film's properties. We therefore test this assumption and its impact on TEMPO layers by studying initial stage growth on multiple material surfaces. We show that whilst plasma polymer growth creates ordered layers on gold and graphite surfaces, there is substantial substrate-dependence with less ordered growth on other materials up to a film thickness of 30 nm, suggesting variation in molecular packing and retention. Beyond that thickness, films convergence to a flat, uniform, surface-agnostic structure. These findings establish the utility of plasma polymerisation as a method for ordered growth and demonstrate the ability to direct the orientation of TEMPO molecules and NO free radicals within a thin film.
MỘT PHƯƠNG PHÁP ĐỊNH VỊ TIÊN ĐỀ CẦN XÓA ĐỂ BẢO ĐẢM TÍNH NHẤT QUÁN TRONG QUÁ TRÌNH TIẾN HÓA ONTOLOGY
Authors: Trung Nguyễn Văn , Nguyễn Thị Bích Lộc
Published: June 2023

Ontology biểu diễn tri thức của một lĩnh vực cụ thể và đóng vai trò quan trọng trong các ứng dụng Web ngữ nghĩa. Khi có sự thay đổi về tri thức của lĩnh vực thì ontology cũng phải được thay đổi – gọi là tiến hóa ontology – thông qua việc bổ sung, chỉnh sửa hoặc xóa các tiên đề để phản ánh tri thức mới. Trong trường hợp ontology hiện tại không nhất quán khi bổ sung các tiên đề mới, người ta sẽ tìm cách chỉnh sửa hoặc xóa một số tiên đề từ ontology hiện tại. Bài báo này đề xuất phương pháp khoanh vùng tập tiên đề cần xóa, sau đó từ tập tiên đề này lựa chọn chính xác tiên đề cần xóa để xây dựng ontology nhất quán trong quá trình tiến hóa ontology.
MỘT SỐ KẾT QUẢ THỰC NGHIỆM XÁC ĐỊNH THÔNG SỐ SÀNG LẮC CỦA MÁY THU HOẠCH CỦ HÀNH TĂM TRÊN ĐẤT CÁT
Authors: Đỗ Minh Cường , Trần Đức Hạnh , Nguyễn Thanh Cường , Nguyễn Thị Ngọc , Phan Tôn Thanh Tâm , Nguyễn Quang
Published: June 2023

Bài báo trình bày một số kết quả thực nghiệm lựa chọn thông số làm việc của cơ cấu sàng phân ly đất cho cho máy thu hoạch củ hành tăm trên đất cát. Một hệ thống sàng lắc đã được thiết lập; hỗn hợp đất – củ hành tăm với ba độ ẩm khác nhau (10, 15 và 20%) được chuẩn bị; một máy biến tần được sử dụng để thay đổi tốc độ động cơ điện nhằm thay đổi tần số lắc của sàng (120, 150 và 180 lần/min); góc nghiêng mặt sàng là 5 và 10°. Để thay đổi đặc điểm làm việc của mặt sàng, chúng tôi bố trí hệ thống lò xo tác động vào tay lắc của sàng nhằm hấp thu lực quán tính của mặt sàng và tạo độ nảy của vật liệu trên sàng. Kết quả cho thấy ở điều kiện: độ ẩm đất 10%, độ cứng lò xo 16,81 N/mm, góc nghiêng mặt sàng 10° và tần số lắc 150 lần/min, hiệu suất phân ly đất là cao nhất; củ hành tăm không nảy lên khỏi mặt sàng; vận tốc di chuyển của củ hành tăm trên mặt sàng đạt 2,5–2,8 km/h, phù hợp với vận tốc tính toán. Kết quả này là cơ sở cho việc thiết kế máy thu hoạch củ hành tăm trên đất cát.
TÌM KIẾM ẢNH THEO NGỮ NGHĨA DỰA TRÊN CẤU TRÚC iRS-TREE VÀ ONTOLOGY
Authors: Lê Thị Vĩnh Thanh , Lê Mạnh Thạnh , Văn Thế Thành
Published: June 2023

Truy xuất hình ảnh theo nội dung được thực hiện dựa trên các đặc trưng cấp thấp và ứng dụng trong nhiều lĩnh vực. Tuy nhiên, thách thức lớn của phương pháp này là khoảng cách ngữ nghĩa giữa các đặc trưng cấp thấp và các khái niệm cấp cao. Vì vậy, bài toán truy xuất hình ảnh theo tiếp cận ngữ nghĩa được quan tâm nghiên cứu nhằm nâng cao độ chính xác truy vấn. Trong bài báo này, chúng tôi đề xuất một mô hình tìm kiếm ảnh và tra cứu ngữ nghĩa dựa trên cấu trúc RS-Tree cải tiến (iRS-Tree) và ontology. Các cải tiến trên iRS-Tree bao gồm: (1) phép toán thêm phần tử nhằm giảm thời gian tạo cây; (2) phép toán tách nút nhằm nâng cao độ chính xác của việc gom cụm dữ liệu. Kết quả của việc truy vấn ảnh trên iRS-Tree là một tập ảnh tương tự và tập từ vựng thị giác. Sau đó, câu lệnh SPAQRL được tự động tạo ra từ tập từ vựng thị giác này và thực hiện truy vấn trên một ontology bán tự động nhằm trích xuất ngữ nghĩa cho hình ảnh. Thực nghiệm được thực hiện trên các tập dữ liệu ảnh: COREL, Oxford Flower-102 và CUB-200-2011. Kết quả thực nghiệm được đánh giá và so sánh với các công trình khác trên cùng một tập dữ liệu nhằm chứng minh tính hiệu quả và đúng đắn của phương pháp đề xuất.
TÌM KIẾM ẢNH ĐA ĐỐI TƯỢNG DỰA TRÊN MẠNG R-CNN VÀ CẤU TRÚC KD-TREE
Authors: Đào Xuân Bao , Nguyễn Thị Định , Nguyễn Phương Hạc , Văn Thế Thành
Published: June 2023

Tìm kiếm ảnh đa đối tượng là một bài toán quan trọng trong lĩnh vực tra cứu ảnh do sự đa dạng và tính phức tạp của hình ảnh. Trong bài báo này, một phương pháp tìm kiếm ảnh đa đối tượng dựa trên mạng R-CNN và cấu trúc KD-Tree được đề xuất nhằm phát triển những ưu điểm của mạng R-CNN trong việc xác định và phân loại từng đối tượng riêng biệt trên ảnh, đồng thời kết hợp với cấu trúc KD-Tree trong việc lưu trữ hình ảnh đã mang lại hiệu suất truy vấn cao và thời gian tìm kiếm ổn định. Để giải quyết bài toán này, chúng tôi trích xuất và phân lớp các đối tượng trên tập dữ liệu hình ảnh bằng mô hình mạng R-CNN và lưu trữ trên cấu trúc KD-Tree. Từ đó, mỗi ảnh đầu vào được phân đoạn theo từng đối tượng, trích xuất vector đặc trưng và thực hiện tìm kiếm tập ảnh tương tự dựa trên cấu trúc KD-Tree. Trên cơ sở đó, một mô hình tìm kiếm ảnh dựa trên mạng R-CNN và cấu trúc KD-Tree được đề xuất. Để minh chứng cho tính đúng đắn của cơ sở lý thuyết đã đề xuất, thực nghiệm được xây dựng trên bộ ảnh COCO với hiệu suất tìm kiếm ảnh là 0,6898. Kết quả thực nghiệm được so sánh với các công trình khác cùng trên bộ dữ liệu; điều này minh chứng cho tính khả thi và hiệu quả của phương pháp đề xuất, đồng thời có thể ứng dụng cho các bộ ảnh đa đối tượng.
Age-Related Changes of the Indicators of Intellectual Development at Various Stages of a Preschool Period
Authors:   Kemerovo State University, Lapteva Yu. A.
Published: June 2023

The article considers common features, interrelation, and sequence of stages in the development of intellectual development components in preschoolers. It has been found that it is reasonable to view the criteria of children’s intellectual development through the assessment of key intellectual acts, extended speech acts, flexibility and liveliness of images and views of natural world. The empirical study of age changes of indicators of intellectual development has been carried out on the sample of 5, 6, and 7-yearolds (n = 199). The study has found difference of average values of indicators of intellectual development in three age groups. The authors have identified the type of the way of development of indicators with the help of the graphic of three points of child’s development. The study has found difference in the value of indicators the child has achieved by a certain age period.
Leadership Potential and Career Orientations as Predictors of Organization Commitment of Newcomers: A Gender Aspect
Authors:   Saint Petersburg State University of Architecture and Civil Engineering, Chernyakevich E. Yu.
Published: June 2023

The article presents the results of the factors that lay behind worker’s commitment to an organization specifying gender differences. The survey was conducted on a sample of 344 newcomers using “Leadership Capabilities Inventory” by E. Zharikova, E. Krushelnitsky, “Career Orientation Test” by E. Shein, “WACMQ” by A. J. S. Morin. The methods of mathematical statistics used in the study – descriptive statistics, Student’s t-test, Pearson correlation coefficient, factor analysis. The study has found correlation among commitment indices (vitality, allegiance, and absorption in an activity), career orientations, and leadership potential; marked differences in the indices of men and women have been found as well. Overall, career perspectives, actualization in organization of leadership capabilities enhance organization commitment of new comers.
Accident Detection and Alert System Using IoT
Authors:   Associate Professor, Department of Electronics & Communication Engineering, Sri Sairam college of Engineering, Anekal, Bengaluru, India, S Jayakumar , Kumar Anil ,   Student, Department of Electronics &  Communication Engineering, Sri Sairam college of Engineering, Anekal, Bengaluru., . Prasanna ,   Student, Department of Electronics &  Communication Engineering, Sri Sairam college of Engineering, Anekal, Bengaluru., . Darshan ,   Student, Department of Electronics &  Communication Engineering, Sri Sairam college of Engineering, Anekal, Bengaluru., . Suhas ,   Student, Department of Electronics &  Communication Engineering, Sri Sairam college of Engineering, Anekal, Bengaluru.
Published: June 2023

Accidents have recently emerged as a major source of concern for humans. Due to a lack of information about the location, magnitude of the accident (or) other issues, some victims cannot be rescued by the response team, which may be an ambulance or police. Many technologies were developed, however they were unable to overcome the problem. However, this project will provide clarification on how to overcome this hurdle. A central system is employed in this project, to which a vibrator sensor, GSM (Global System for Mobile Communications), and GPS modules are attached. To prevent detecting errors, numerous sensors are strategically distributed throughout the vehicle. After an accident takes place the vibrator sensor becomes active, and GPS (Global Positioning System) is engaged with the assistance of the central system GSM ( Global System for Mobiles ). Immediately, alert messages will be handed down to the response teams, outlining the live location and severity of the accident
Computer Aided Medical Bed
Authors:   Assistant Professor, Department of Electronics & Communication Engineering, Sri Sairam college of Engineering, Anekal, Bengaluru, India, Shubraja Hema , D Pagade Sandeep ,   Student, Department of Electronics & Communication Engineering,  Sri Sairam college of Engineering, Anekal, Bengaluru, India, S Mithun ,   Student, Department of Electronics & Communication Engineering,  Sri Sairam college of Engineering, Anekal, Bengaluru, India, A Prajwal ,   Student, Department of Electronics & Communication Engineering,  Sri Sairam college of Engineering, Anekal, Bengaluru, India
Published: June 2023

Background and goal: Being bedridden long-term can motive deterioration in sufferers’ physiological feature and overall performance, restricting each day sports and growing the prevalence of falls and different unintentional injuries. Little research has been carried out in designing effective detecting systems to screen the posture and status of bedridden sufferers and to provide correct real-time comments on posture. The functions of these studies were to develop a laptop-aided gadget for actual-time detection of bodily sports in bed and to validate the system’s validity and check–retest reliability in determining 8 postures: movement leftward/rightward, turning over leftward/rightward, getting up leftward/rightward, and getting out of bed leftward/rightward. Strategies: The in-bed physical interest detecting system consists specifically of a clinical sickbed, signal amplifier, a records acquisition (DAQ) machine, and working software program for computing and figuring out postural modifications related to four load cellular sensing components. Thirty healthy subjects (15 males and 15 ladies, suggest age = 27.8 ± 5.3 years) participated within the look at. All topics were asked to execute eight in-bed sports in a random order and to take part in an evaluation of the take a look at–retest reliability of the outcomes 14 days later. Spearman’s rank correlation coefficient was used to examine the gadget’s determinations of postural states with researchers’ recordings of postural modifications. The test–retest reliability of the gadget’s potential to decide postures was analyzed the use of the interclass correlation coefficient ICC(three,1). Consequences: The machine was determined to show off excessive validity and accuracy (r = zero.928, p < zero.001; accuracy rate: 87.nine %) in determining in-bed displacement, turning over, and sitting up, and getting out of bed. The machine become mainly correct in detecting motion rightward (ninety %), turning over leftward (83%), sitting up leftward or rightward (87–93%), and getting out of bed (100%). The test–retest reliability ICC (three,1) fee was 0.968 (p < zero.001).
IoT Baby Monitoring System Using Node MCU
Authors:   Assistant Professor, Department of Electronics & Communication Engineering, Sri Sairam college of Engineering, Anekal, Bengaluru, India, S Geetha , . Venkatakrishnan , . Shanmugam , . Neejashwini , . Iniyan
Published: June 2023

This paper presents an idea to design a Smart Cradle System using IOT which will help the parents to monitor their child even if they are away from home & detect every activity of the Baby from any distant corner of the world. It is an innovative, smart & protective Cradle System to nurture an infant in an efficient way. This system considers all the minute details required for the care & protection of the Baby in the cradle. The design of smartness & innovation comes with the use of technologies/methodologies which include the Internet of Things (IoT) (Modules like Arduino UNO, Humidity & Temperature sensing, etc..,), Cry Detecting Mechanism, Live Video Surveillance, Cloud Computing (Data Storage) & User Friendly Web application (for User Controls). In order to detect each & every activity of the Baby, different Sensors/Modules are attached to the Cradle: Humidity & Temperature Sensing Module for detection of Wetness of the bed, A Camera on top of the Cradle for live video footage & Cry Detection Circuit to analyze Cry Patterns. All the data which has been taken from the sensors/modules will be stored in Cloud? & analyzed at regular intervals.
Examination Scheduling for an Educational Institution that follows a Choice-based credit system
Authors:   Assistant Professor, Dept of CSE, Sri Sairam College of Engineering, Bengaluru, India, V.A Guruprasath , P Bhavana , A Anusha , . Patil , C Chaithra
Published: June 2023

Examination scheduling is a common as well as an important activity in an educational institution. In examination scheduling, courses are allocated a time slot in such a way that no student is assigned to attend more than one examination at a time. Further, the scheduling includes allocation of physical resources like exam room, invigilator to an examination without any conflicts. The complexity of an examination scheduling depends on many factors like nature of educational program, number of students, number of staff, time limit and availability of other resources. In this study, we developed a solution for examination scheduling in an educational system that follows a choice-based credit system. We used heuristic searching in multiple stages to arrive an optimal solution. We used Prolog, a logical programming language, SQL, PHP and HTML to develop this software. Also in this solution we limit ourselves to allocation of time slots to a course and we don’t include allocation of other physical resources like class rooms, invigilators.
Smart Wearable Device for Women Safety Using IoT
Authors:   Assistant Professor, Department of CSE, Sri Sairam College of Engineering, Anekal, Bengaluru, India, K N Nandini , R Mounicca , I Madhumitha , J Kirthivasa
Published: June 2023

The crimes against women have been rising significantly and often hear about molestation, eve teasing and rape cases in the public places of the society. The security of women is the most important concern these days and to build a safety device to act as a rescue and to prevent from harm at the time of hazard is highly necessary especially for women. In this paper, a smart device for women’s safety which automates the emergency alert system by using pressure sensor, pulse-rate sensor and temperature sensor to detect a possible atrocity automatically using outlier detection is proposed. This system detects and sends the alerts for the dear ones with the location coordinates of the women without the requirement other interaction in critical times. It sends an emergency message automatically to the relatives and nearby police station.
Automated Brain Segmentation and Classification of Tumor through Robotics and Machine Learning
Authors:   Assistant Professor, Department of CSE,  Sri Sairam College of Engineering, Bangalore, India, K Radhika , Pandit Sudhanshu , Lakshmi Shri , B Sandeep
Published: June 2023

The process of neurosurgery is delicate and time consuming, often resulting in lower patient outcomes and survival rates. Therefore, we are implementing computer algorithms for the classification and segmentation of brain tumors. This aims to improve the accuracy of identifying tumor and segmentation of the brain. The automatic segmentation of the brain is based on CT (Computed tomography) data using the Desktop Image Processing System (DISOS). The DISOS system integrates modules such as preoperative planning and user guidance. Automated segmentation algorithms, including fuzzy c means clustering method, intensity thresholding, region growing, level set methods, and machine learning approaches, are employed to segment the brain structures. This system demonstrates improved accuracy, robustness, and efficiency, although a final check by a medical expert is still necessary. Additionally, our paper highlights the use of advanced algorithms and machine learning techniques to differentiate between cancerous and non-cancerous tumors using various medical imaging data. The incorporation of genetic, molecular, and clinical data further enhances the accuracy of tumor classification models. Challenges in real time robot path planning and navigation for neurosurgery are addressed, including the use of A-mode ultrasound and augmented reality systems to provide enhanced guidance during procedures. This study concludes by emphasizing the collaboration between medical professionals and computer scientists in advancing the field of computer-assisted brain tumor diagnosis and robot-assisted surgery. Our goal is not to replace humans with robots, but the collaboration between them for incredible outcomes.
Al6061-Basalt and Zircon Hybrid composite Material Corrosion Resistance in Acid Media
Authors:   Department of Chemistry, Sri Sairam College of Engineering, Bangalore, India, Krishna Hari , Balan Sivasakti , Babu Harish
Published: June 2023

The present investigation is an attempt made to develop Al6061/Basalt/Zirconium oxide Hybrid Metal Matrix Composites (MMCs) by liquid metallurgy technique (stir casting) and to study the wear properties of Al6061/Basalt/Zirconium oxide reinforced hybrid metal matrix composites. The composite is prepared by using Liquid Metallurgy Route (Stir Casting Technique), although other processing technique such as powder metallurgy delivers better mechanical properties in MMCs, Liquid state has some significant focal points, for example, better matrix molecule holding, simpler control of matrix structure, ease of handling, closer to net shape and wide choice of material. Al6061 is taken as a base material (matrix) and Basalt (1– 10%) and Zirconium oxides (2%) are used as reinforcements. Corrosion analysis for Aluminum Metal Matrix Composites (MMCs) was done in acid (HCl) media at room temperature & different time intervals. The results were tabulated & it was found that the MMC containing 4% basalt underwent maximum corrosion at room temperature. SEM is done for all the samples the results are tabulated.
Cell Disease Identification Using Enhanced Salp Swarm Algorithm in Machine Learning
Authors:   Associate Professor, St Xavier’s Catholic college of Engineering, Muthu Felix Xavier , M Angelin Rosy , S Elamathi , S Alfiya , R Vigneshwari
Published: June 2023

Computerized diagnosis of white blood cells cancer diseases for instance Leukemia and Myeloma is a demanding biomedical research area. Our method presents for the first time a new state of the application that assists in diagnosing the white blood cells diseases. We divide these diseases into two types; each type includes similar symptoms a disease that may my method is applied on one of the two diseases category by computing different features. Finally, Random Forest classifier is enforced for final decision. The proposed method aims to early discovery of white blood cells cancer, reduce the misdiagnosis cases in adding up to develop the system learning methodology. Moreover, allowing the experts only to have the final modification on the result obtained from the system. The proposed approach achieved an accuracy of 93% in the first type and 95% in the second type.
Blockchain and its Applications NFT’s: Use of Blockchain Security in the NFT Marketplace
Authors:   Assistant professor, Dept of CSE Sri Sairam College of Engineering Anekal, Bangalore, India, . Suguna , V Thanuj , hunagund Shashank , M Yashanth
Published: June 2023

In the current time’s, Blockchain or most commonly known as blockchain technology which is a distributed software network and a secure network that allows the secure transfer of assets without any intermediate and has made a huge hype in the digital market or in the internet market place and is taking over like a breeze with its secure and easier transactions, mostly transactions done with the cryptocurrencies like bitcoin ,etherum, etc , with the help of these methods the transactions can be kept out of the books or the papers , where NFT(Non fungible token) is a unique token with its unique characteristics, it is a unique digital art with which is traded on the blockchain network and etherum network including the etherum environment as the front end with the help of this front end system they can trade within the network using etherum coins on platform such as open sea where digital assests are listed , auctioned and traded for the secure transaction of these NFT it uses blockchain network to do the transactions more efficiently. Throughout this research all the required information about the Blockchain and its applications, NFT’s: Use of blockchain Security in the NFT marketplace is listed out.
Early Prediction of Cardiac Arrest Using Data Mining Algorithms
Authors:   Assistant Professor, Department of CSE, Sri Sairam College of Engineering, Anekal, Bangalore, India, Kumar Ram , Gupta Tannya , Meshram Yamini , Kumari Juhi
Published: June 2023

Cardiac arrest is a sudden and unexpected loss of heart function that can lead to death. Early prediction of cardiac arrest could help to improve survival rates by allowing for early intervention. Datamining is a field of computer science that involves the extraction of knowledge from large datasets. Data mining algorithms can be used to identify patterns in data that may be indicative of cardiac arrest. For example, data mining algorithms can be used to identify patients who are at increased risk of cardiac arrest based on their medical history, lifestyle factors, and other characteristics. This paper reviews the use of data mining algorithms for early prediction of cardiac arrest. The paper discusses the different data mining algorithms that have been used for this purpose, as well as the results of studies that have evaluated the effectiveness of these algorithms. The paper also discusses the challenges of using data mining for early prediction of cardiac arrest, and the future directions of research in this area. The paper concludes that data mining algorithms have the potential to improve early prediction of cardiac arrest. However, more research is needed to develop more accurate and reliable data mining algorithms. Additionally, more research is needed to develop methods for integrating data mining algorithms into clinical practice.
Facial Emotion Recognition System for Isolated Patient Monitoring using ResNet-50 based Convolutional Neural Network Model
Authors:   Department of Computer Science,  Sri Sairam College of Engineering, Bengaluru, India, V Yamuna , S Yashaswini , R Neelaveni , J Ranjitha
Published: June 2023

Facial emotion recognition is a promising technology that has the potential to improve the quality of care for isolated patients by enabling healthcare professionals to assess the emotional state of these patients more accurately. Isolated patient monitoring is the practice of closely observing patients who have been isolated due to the risk of infection or other health concerns, and it is essential to ensure the well-being of these patients. The Facial Expression Recognition system is the process of identifying the emotional state of a person. In this system, captured image is compared with the trained dataset available in database and then emotional state of the image will be displayed. This will also integrate the system into existing patient monitoring systems and collect data on its effectiveness in improving the care and well-being of isolated patients. The ultimate goal is to demonstrate the value of facial emotion recognition in isolated patient monitoring, and to identify any potential ethical or privacy concerns that may need to be addressed. This is for facial emotion recognition (FER) in isolated patient monitoring. FER is achieved using computer vision techniques and voice recognition techniques to analyze and interpret facial expressions, which can be useful for identifying and tracking changes in patient’s emotional states. The proposed FER system utilizes deep learning algorithms for real-time detection and classification of emotions with high accuracy. Two popular methods utilized mostly in the literature for the automatic FER systems are based on geometry and appearance. Facial Expression Recognition usually performed in three-stages consisting of pre-processing, face detection & feature extraction, and expression classification. The paper analyses various deep learning image classification models (convolutional neural networks) to identify the certain human emotions: depressed, despair, fear, irritated, uneasy, shocked and neutrality.
A Smart Car Rental Management System using Data Mining
Authors:   Professor, Department of CSE, Sri Sairam College of Engineering, Bangalore, India, A Mahesh , C Neelavathi , N Monika , J Joiceline , Priya Rubini
Published: June 2023

The car rental management system is a comprehensive software application designed to help car rental companies manage their operations efficiently. It includes features such as vehicle registration, inventory management, pricing management, billing and invoicing, customer management, and reporting. The system provides a user-friendly interface for customers to search for available vehicles, make reservations, and manage their bookings. The CRMS encompasses a comprehensive suite of features aimed at automating and optimizing various aspects of car rental operations. These include customer registration and authentication, vehicle inventory management, reservation handling, rental duration tracking, payment processing, and reporting functionalities. By integrating these components into a unified platform, the CRMS simplifies and streamlines the entire rental process, enabling car rental companies to operate efficiently and deliver a superior customer experience. Key benefits of the CRMS include improved operational efficiency, enhanced accuracy in managing rental bookings, minimized administrative tasks, and reduced paperwork. Customers can conveniently browse vehicle options, make reservations, and complete transactions through user-friendly interfaces, fostering a seamless and hassle-free rental experience. Additionally, the car rental management system provides reporting and analytics features, enabling the company to analyse rental patterns, track revenue, and monitor performance metrics. This information can help in making informed business decisions, optimizing fleet utilization, and enhancing customer satisfaction. Overall, the car rental management system streamlines operations, improves efficiency, and enhances customer service in the car rental industry by automating key processes and providing real-time access to crucial information.
Leveraging Artificial Intelligence in Education: Transforming the Learning Landscape
Authors:   Lecturer, Department of Computer Science Akshara First Grade College, Anekal, N C Ashwini , Kumar Naveen , M Nandan , V Suman
Published: June 2023

This article explores the transformative potential of Artificial Intelligence (AI) in the field of education, with a focus on personalized learning. AI technologies can analyze vast amounts of data, adapt to individual needs, and provide tailored learning experiences for students. By leveraging AI in education, we can unlock the power of personalized learning, leading to improved student outcomes, increased engagement, and enhanced educational experiences. This article discusses the benefits, challenges, and future implications of AI in education, highlighting the importance of ethical considerations and responsible implementation to ensure equitable access to quality education for all learners.
Smart Anti-Burglary Surveillance System using Image AI
Authors:   Asst.Professor, Department of CSE Sri Sairam College of Engineering, Anekal, Bangalore, Karnataka, India, Thomas Reji , Sundaram Arvind , Rajesh RajPragya , Shree Navya
Published: June 2023

In today's world, with an increasing number of robberies, looting and shoplifting, it is indispensable to ensure the safety of our belongings and valuables. When it comes to certain places like bank vaults, uninhabited houses, business establishments like retail shops, jewellery stores, watch stores, etc., surveillance for observing the premise is very essential and has become the unavoidable need of the hour. At such places, it is unlikely to continuously monitor the venue using conventional cameras or a security guard person. To address such type of issues which involve uncertainty of safety, our project proposes a system which will tirelessly monitor the venue at required hours, intimate the intended person (administrator) via mobile communication (Short Message Service), initiate an alert alarm at the premise in order to aware the surroundings and also save the intrusion detected frames in the specified choice of storage. Also, it is developed in such a manner that the system recognizes and does not initiate alert/notification for persons those who are reliable and trustworthy (such as the shopkeeper, habitant of the house, etc.). This system is implemented with specific considerations using Image AI and Tensor flow built upon Convolutional Neural Networks, remotely operatable by users, without compromising the importance of security and protection.