Search results for: textile machine

Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

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In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: hierarchical temporal memory, HTM, learning algorithms, machine learning, spatial pooler

Procedia PDF Downloads 343

Authors: Josef Brychta, Jiri Kratochvil, Marek Pagac

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The group of progressive cutting materials can include non-traditional, emerging and less-used materials that can be an efficient use of cutting their lead to a quantum leap in the field of machining. This is essentially a “superhard” materials (STM) based on polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) cutting performance ceramics and development is constantly "perfecting" fine coated cemented carbides. The latter cutting materials are broken down by two parameters, toughness and hardness. A variation of alloying elements is always possible to improve only one of each parameter. Reducing the size of the core on the other hand doing achieves "contradictory" properties, namely to increase both hardness and toughness.

Keywords: grained cutting materials difficult to machine materials, optimum utilization, mechanic, manufacturing

Procedia PDF Downloads 299

Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: Sheng-Tse Wu, Wu-Sung Yao

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In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

Procedia PDF Downloads 395

Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek

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This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.

Keywords: autonomous maritime vehicle, object detection, situation awareness, tracking

Procedia PDF Downloads 455

Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

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Sponsored search is a multi-billion dollar industry and makes up a major source of revenue for search engines (SE). Click-through-rate (CTR) estimation plays a crucial role for ads selection, and greatly affects the SE revenue, advertiser traffic and user experience. We propose a novel architecture of solving CTR prediction problem by combining artificial neural networks (ANN) with decision trees. First, we compare ANN with respect to other popular machine learning models being used for this task. Then we go on to combine ANN with MatrixNet (proprietary implementation of boosted trees) and evaluate the performance of the system as a whole. The results show that our approach provides a significant improvement over existing models.

Keywords: neural networks, sponsored search, web advertisement, click prediction, click-through rate

Procedia PDF Downloads 572

Authors: Omar Imhemed Alramli

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As Transmission Control Protocol (TCP), User Datagram Protocol (UDP) is transfer protocol in the transportation layer in Open Systems Interconnection model (OSI model) or in TCP/IP model of networks. The UDP aspects evaluation were not recognized by using the pcattcp tool on the windows operating system platform like TCP. The study has been carried out to find a tool which supports UDP aspects evolution. After the information collection about different tools, iperf tool was chosen and implemented on Cygwin tool which is installed on both Windows XP platform and also on Windows XP on virtual box machine on one computer only. Iperf is used to make experimental evaluation of UDP and to see what will happen during the sending the packets between the Host and Guest in wired and wireless networks. Many test scenarios have been done and the major UDP aspects such as jitter, packet losses, and throughput are evaluated.

Keywords: TCP, UDP, IPERF, wireless LAN

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Authors: Stephanie Lehmann, Esther Ruf, Sabina Misoch

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Background: Due to demographic change and shortage of skilled nursing staff, assistive robots are built to support older adults at home and nursing staff in care institutions. When assistive robots facilitate tasks that are usually performed by humans, user acceptance is essential. Even though they are an important aspect of acceptance, emotions towards different assistive robots and different situations of robot-use have so far not been examined in detail. The appearance of assistive robots can trigger emotions that affect their acceptance. Acceptance of robots is assumed to be greater when they look more human-like; however, too much human similarity can be counterproductive. Regarding different groups, it is assumed that older adults have a more negative attitude towards robots than younger adults. Within the framework of a simulated robot study, the aim was to investigate emotions of older adults compared to students towards robots with different appearances and in different situations and so contribute to a deeper view of the emotions influencing acceptance. Methods: In a questionnaire study, vignettes were used to assess emotions toward robots in different situations and of different appearance. The vignettes were composed of two situations (service and care) shown by video and four pictures of robots varying in human similarity (machine-like to android). The combination of the vignettes was randomly distributed to the participants. One hundred forty-two older adults and 35 bachelor students of nursing participated. They filled out a questionnaire that surveyed 30 positive and 30 negative emotions. For each group, older adults and students, a sum score of “positive emotions” and a sum score of “negative emotions” was calculated. Mean value, standard deviation, or n for sample size and % for frequencies, according to the scale level, were calculated. For differences in the scores of positive and negative emotions for different situations, t-tests were calculated. Results: Overall, older adults reported significantly more positive emotions than students towards robots in general. Students reported significantly more negative emotions than older adults. Regarding the two different situations, the results were similar for the care situation, with older adults reporting more positive emotions than students and less negative emotions than students. In the service situation, older adults reported significantly more positive emotions; negative emotions did not differ significantly from the students. Regarding the appearance of the robot, there were no significant differences in emotions reported towards the machine-like, the mechanical-human-like and the human-like appearance. Regarding the android robot, students reported significantly more negative emotions than older adults. Conclusion: There were differences in the emotions reported by older adults compared to students. Older adults reported more positive emotions, and students reported more negative emotions towards robots in different situations and with different appearances. It can be assumed that older adults have a different attitude towards the use of robots than younger people, especially young adults in the health sector. Therefore, the use of robots in the service or care sector should not be rejected rashly based on the attitudes of younger persons, without considering the attitudes of older adults equally.

Keywords: emotions, robots, seniors, young adults

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Authors: Benchalak Muangmeesri

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The purpose of this paper is to discuss how to test the best control performance of a ceramics. Hydraulic press machine (HPM) is the most common shaping of advanced ceramic with products, dimensions, and ceramic products mainly from synthetic powders. A microcontroller can be achieved to control process and has set high standards in the shaping of raw materials in powder form. HPM was proposed to develop a position control system that linked to the embedded controller PIC16F877 via Proportional and Derivative (PD) controller. The model is performed using MATLAB/SIMULINK and the best control performance of an HPM. Finally, PD controller results, showing the best performance as it had the smallest overshoot and highest quality using a microcontroller control.

Keywords: ceramics, hydraulic press, microcontroller, PD controller

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Authors: Senthuran Manoharan, Rathesan Sivagananalingam

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One of the main issues in system security is Authentication. Authentication can be defined as the process of recognizing the user's identity and it is the most important step in the access control process to safeguard data/resources from being accessed by unauthorized users. The static method of authentication cannot ensure the genuineness of the user. Due to this reason, more innovative authentication mechanisms came into play. At first two factor authentication was introduced and later, multi-factor authentication was introduced to enhance the security of the system. It also had some issues and later, adaptive authentication was introduced. In this research paper, the design of an adaptive authentication engine was put forward. The user risk profile was calculated based on the user parameters and then the user was challenged with a suitable authentication method.

Keywords: authentication, adaptive authentication, machine learning, security

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Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: I Lamri, L Arabet, M. Hidjeb

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The direct shear test was used to determine the shear strength parameters C and Ø of a series of samples with different cement content. Samples stabilized with a certain percentage of cement showed a substantial gain in compressive strength and a significant increase in shear strength parameters. C and Ø. The laboratory equipment used in UCS tests consisted of a conventional 102mm diameter sample triaxial loading machine. Beyond 4% cement content a very important increase in shear strength was observed. It can be deduced from a comparative study of shear strength of soil samples with 4%, 7%, and 10% cement with sample containing 2 %, that the sample with a 4% cement content showed 90% increase in shear strength while those with 7% and 10% showed an increase of around 13 and 21 fold.

Keywords: cement, compression strength, shear stress, cohesion, angle of internal friction

Procedia PDF Downloads 485

Authors: Emre Kara, Metehan Demir, Şura Karakuzu, Kadir Koç, Ahmet F. Geylan, Halil Aykul

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While the polymeric foam cored sandwiches have been realized for many years, recently there is a growing and outstanding interest on the use of sandwiches consisting of aluminum foam core because of their some of the distinct mechanical properties such as high bending stiffness, high load carrying and energy absorption capacities. These properties make them very useful in the transportation industry (automotive, aerospace, shipbuilding industry), where the "lightweight design" philosophy and the safety of vehicles are very important aspects. Therefore, in this study, the sandwich panels with aluminum alloy foam core and various types and thicknesses of glass fiber reinforced polymer (GFRP) skins produced via Vacuum Assisted Resin Transfer Molding (VARTM) technique were obtained by using a commercial toughened epoxy based adhesive with two components. The aim of this contribution was the analysis of the bending response of sandwiches with various glass fiber reinforced polymer skins. The three point bending tests were performed on sandwich panels at different values of support span distance using a universal static testing machine in order to clarify the effects of the type and thickness of the GFRP skins in terms of peak load, energy efficiency and absorbed energy values. The GFRP skins were easily bonded to the aluminum alloy foam core under press machine with a very low pressure. The main results of the bending tests are: force-displacement curves, peak force values, absorbed energy, collapse mechanisms and the influence of the support span length and GFRP skins. The obtained results of the experimental investigation presented that the sandwich with the skin made of thicker S-Glass fabric failed at the highest load and absorbed the highest amount of energy compared to the other sandwich specimens. The increment of the support span distance made the decrease of the peak force and absorbed energy values for each type of panels. The common collapse mechanism of the panels was obtained as core shear failure which was not affected by the skin materials and the support span distance.

Keywords: aluminum foam, collapse mechanisms, light-weight structures, transport application

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Authors: Min Wu, Shuming Shen, Xuhong Yang, Rencheng Tang

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Every year, numerous organic wastes from fiber byproducts of the wool textile industry, poor quality raw wools not fit for spinning, horns, nails and feathers from butchery are disposed. These wastes are abundant in keratin which is a renewable material. Wool fiber/keratin/PVA composites with different proportions were prepared in this study, and the influence of the proportions on their structure and properties were studied, aiming to understand the potential application of keratin in the field of biomedicine, degradable wrapper, and cosmetics film, and provide a new way to reuse keratin wastes. The urea / sodium sulfide / sodium dodecyl sulfate (SDS) method was used to dissolve the wool. After filtration and dialysis, the wool keratin solution was achieved. Then the keratin solution and polyvinal (PVA) solution were blended in different proportions, and the wool fibers cut into a certain length were cast into the blended solution. Thereby, various wool fiber/keratin/PVA composite films with different proportions were formed through pouring the solution into a flat box and drying at room temperature. The surface morphology, molecular structure, and mechanical property of the composite films were studied. The results showed that, there are α-helix structure, β-sheet and random coil conformations in the pure keratin film, as well as in the wool fiber. Compared with wool fiber, the crystallinity of keratin decreased. PVA can obviously improve the mechanical property of the blended film. When the blended ratio of keratin and PVA is 20:80, the mechanical property of the blended film is greatly improved. The composite films with 8%-16% of wool fibers have better flexibility than those without wool fibers.

Keywords: composite film, keratin, mechanical property, morphological structure, PVA, wool fiber

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Authors: T. Malmir, U. Eicker

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Landfilling of organic waste is still the predominant waste management method in the USA and Canada. Strategic plans for waste diversion from landfills are needed to increase material recovery and energy generation from waste. In this paper, we carried out a statistical survey on waste flow in the two cities New York and Montréal and estimated the energy recovery potential for each case. Data collection and analysis of the organic waste (food waste, yard waste, etc.), paper and cardboard, metal, glass, plastic, carton, textile, electronic products and other materials were done based on the reports published by the Department of Sanitation in New York and Service de l'Environnement in Montréal. In order to calculate the gas generation potential of organic waste, Buswell equation was used in which the molar mass of the elements was calculated based on their atomic weight and the amount of organic waste in New York and Montréal. Also, the higher and lower calorific value of the organic waste (solid base) and biogas (gas base) were calculated. According to the results, only 19% (598 kt) and 45% (415 kt) of New York and Montréal waste were diverted from landfills in 2017, respectively. The biogas generation potential of the generated food waste and yard waste amounted to 631 million m³ in New York and 173 million m³ in Montréal. The higher and lower calorific value of food waste were 3482 and 2792 GWh in New York and 441 and 354 GWh in Montréal, respectively. In case of yard waste, they were 816 and 681 GWh in New York and 636 and 531 GWh in Montréal, respectively. Considering the higher calorific value, this amount would mean a contribution of around 2.5% energy in these cities.

Keywords: energy recovery, organic waste, urban energy modelling with INSEL, waste flow

Procedia PDF Downloads 135

Authors: Irfan Ahmad, Raza Ghafoor, Hammad Raza Ahmad, Muhammad Asif, Farrakh Nawaz, M. Tahir Siddiqui

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Due to the exploding population of Pakistan the pressure on natural forests is increasing to meet the demands of wood and wood based products. Agroforestry is being practiced throughout the world on scientific basis but unfortunately the farmers of Pakistan are reluctant in its adoption. The presents study was designed to assess the adoption of agroforestry practices in Faisalabad with respect to land holdings of farmers and future suitability by using Geographic information system (GIS). Faisalabad is the third largest city of the country and is famous due to the textile industry. A comprehensive survey from target villages of the Lyallpur town of Faisalabad district was carried out. Out of total 65 villages, 40 were selected for study. From each selected village, one farmer who was actively engaged in farming activities was selected. It was observed that medium sized farmers having 10-20 acre were more in number as compared to small and large farmers. Number of trees was found maximum in large farm lands, ratio of diseased trees was almost similar in all categories with maximum in small farmlands (24.1%). Regarding the future prospects 35% farmer were interested in agroforestry practices 65% were not interested in the promotion of trees due to the non-availability of technical guidance and proper markets. Geographic images of the study site can further help the researchers and policy makers in the promotion of agroforestry.

Keywords: agroforestry trends, adoption, Faisalabad, geographic information system (GIS)

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

Procedia PDF Downloads 246

Authors: Bashir Aliyu Yauri, Rufai Aliyu Yauri

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With the introduction of cash-less society policy by the Central Bank of Nigeria, the concept of e-banking services has experienced a significant improvement over the years. Today quite a number of people are embracing e-banking activities especially ATM, thereby moving away from the conventional banking system. This paper presents a review of the underlying Architectural Layout of Intra-Bank and Inter-Bank ATM connectivity in Nigeria. The paper further investigates and discusses factors affecting the Intra-Bank and Inter-Bank ATM connectivity in Nigeria. And as well possible solutions to these factors affecting ATM Connectivity and Operations are proposed.

Keywords: architectural layout, automated teller machine, e-services, postilion

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Authors: M. N. Osman Zahid, K. Case, D. Watts

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This paper reports an advanced approach in the application of CNC machining for rapid manufacturing processes (CNC-RM). The aim of this study is to improve the quality of machined parts by introducing different cutting tools during finishing operations. As the cutting is performed in different directions, the surfaces presented on part can be classified into several categories. Therefore, suitable cutting tools are assigned to machine particular surfaces and to improve the quality. Experimental studies have been carried out by fabricating several parts based on the suggested approach. The results provide further support for implementing this approach in rapid machining processes.

Keywords: CNC machining, end mill tool, finishing operation, rapid manufacturing

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Authors: O. B. Urhibo, D. Imhonopi, T. George

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The global rate of decline in entrepreneurial activities, and the prevalence in Africa, especially Nigeria, is more worrisome. In recent times, these problems, such as the lack of accessibility and utilization of financial incentives needed to promote entrepreneurial activities, have led to a decrease in entrepreneurial activities. The causes of the decline have been evaluated from a different perspective and have further confirmed the relevance and need for the sustainability of the Fashion industry. With the increasing rate of unemployment and poverty in Nigeria and the literature gap in the social context, this study investigated the patterns of sustainable financial incentives utilisation among fashion design entrepreneurs in Nigeria through a qualitative approach. The Eastern part of Nigeria was considered in this study because of the high rate of market activity for textile and clothing firms. Specifically, Delta state was considered in this study. A purposive sampling technique was used to select key informants consisting of twelve (12) executives of the associations (i.e., Fashion Designer & Exhibitors Association, Delta Fashion Designers, and Fashion Designers Association of Nigeria for the interview sessions. Four themes emanate from the thematic analysis -lack of sufficient collateral, difficulties and duration of loan application processes, unacceptable business proposal/plan, and the absence of audited financial accounts were found to be the patterns of sustainable financial incentives utilisation among fashion design entrepreneurs in Nigeria. The promotion of sustainable patterns and supports has been suggested to reduce the challenges of sustainable financial incentives utilisation among fashion design entrepreneurs.

Keywords: entrepreneurship, fashion design, financial incentives, patterns, sustainability, utilisation

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Authors: Jawharah Alasmari

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In verb inflection, tense marks past/present/future action, and aspect marks progressive/continues perfect/completed actions. This usage and meaning of tense and aspect differ in Arabic and English. In this research, we applied data mining methods to test the predictive function of candidate features by using our dataset of Arabic verbs in-context, and their 7 translations. Weka machine learning classifiers is used in this experiment in order to examine the key features that can be used to provide guidance to enable a translator’s appropriate English translation of the Arabic verb tense and aspect.

Keywords: Arabic verb, English translations, mining methods, Weka software

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Authors: Manoj Gupta Charan Pushparaj

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Tourism related activities are getting popular day by day and tourism has become an integral part of everyone’s life. Ecotourism initiatives have grown enormously in the past decade, and the concept of ecotourism has shown to bring great benefits in terms of environment conservation and to improve the livelihood of local people. However, the potential of ecotourism to sustain improving the livelihood of the local population in the remote future is a topic of active debate. A primary challenge that exists in this regard is the enormous costs of limiting the impacts of tourism related activities on the environment. Here we employed systems modeling approach using computer simulations to determine if ecotourism activities in the small hill town of Yercaud (Tamil Nadu, India) can be sustained over years in improving the livelihood of the local population. Increasing damage to the natural environment as a result of tourism-related activities have plagued the pristine hill station of Yercaud. Though ecotourism efforts can help conserve the environment and enrich local population, questions remain if this can be sustained in the distant future. The vital state variables in the model are the existing tourism foundation (labor, services available to tourists, etc.,) in the town of Yercaud and its natural environment (water, flora and fauna). Another state variable is the textile industry that drives the local economy. Our results would help to understand if environment conservation efforts are sustainable in Yercaud and would also offer suggestions to make it sustainable over the course of several years.

Keywords: ecotourism, simulations, modeling, Yercaud

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Hikmet Cicek

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Metal nitrides show excellence tribological properties and they used for especially on machine parts. In this work, the vacuum gas nitriding proses were applied to the titanium, D2 and 52100 steel substrates at three different proses temperatures (500 °C, 600°C and 700 °C). Structural, mechanical and tribological properties of the samples were characterized. X-Ray diffractometer, scanning electron microscope and energy dispersive spectroscopy analyses were conducted to determine structural properties. Microhardness test and pin-on-disc wear test were made to observe tribological properties. Coefficient of friction, wear rate and wear traces were examined comparatively. According to the test results, the process temperature very effective parameter for the vacuum gas nitriding method.

Keywords: gas nitriding, tribology, wear, coating

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Authors: Pyi Phyo Maung

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In the study, the calculations of the permeability coefficient, values of the volume and porosity of a unit cell of a woven fabric before and after deformation based on the geometrical parameters are presented. Two types of carbon woven fabric structures were investigated: standard type, which integrated the filament, has a cross sectional shape of a cylinder and spread tow type, which has a rectangular cross sectional shape. The space antennas reflector, which distinctive feature is the presence of the surface of double curvature, is considered as the object of the research. Modeling of the kinetics of the process of impregnation of the reflector for the two types of carbon fabric’s unit cell structures was performed using software RAM-RTM. This work also investigated the influence of the grid angle between warp and welt of the unit cell on the duration of impregnation process. The results showed that decreasing the angle between warp and welt of the unit cell, the decreasing of the permeability values were occurred. Based on the results of calculation samples of the reflectors, their quality was determined. The comparisons of the theoretical and experimental results have been carried out. Comparison of the two textile structures (standard and spread tow) showed that the standard textiles with circular cross section were impregnated faster than spread tows, which have a rectangular cross section.

Keywords: vacuum assistant resin infusion, impregnation time, shear angle, reflector and modeling

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Authors: Jung-Min Yang

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Fault diagnosis of composite asynchronous sequential machines with parallel composition is addressed in this paper. An adversarial input can infiltrate one of two submachines comprising the composite asynchronous machine, causing an unauthorized state transition. The objective is to characterize the condition under which the controller can diagnose any fault occurrence. Two control configurations, state feedback and output feedback, are considered in this paper. In the case of output feedback, the exact estimation of the state is impossible since the current state is inaccessible and the output feedback is given as the form of burst. A simple example is provided to demonstrate the proposed methodology.

Keywords: asynchronous sequential machines, parallel composition, fault diagnosis, corrective control

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

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Authors: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Abdul Basit Kiani

Abstract:

Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

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