Search results for: myoelectric signal processing

Authors: Mosab Alrashed, Wei Xu, Stephen Abineri, Yifan Zhao, Jörn Mehnen

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Thermographic inspection is a relatively new technique for Non-Destructive Testing (NDT) which has been gathering increasing interest due to its relatively low cost hardware and extremely fast data acquisition properties. This technique is especially promising in the area of rapid automated damage detection and quantification. In collaboration with a major industry partner from the aerospace sector advanced thermography-based NDT software for impact damaged composites is introduced. The software is based on correlation analysis of time-temperature profiles in combination with an image enhancement process. The prototype software is aiming to a) better visualise the damages in a relatively easy-to-use way and b) automatically and quantitatively measure the properties of the degradation. Knowing that degradation properties play an important role in the identification of degradation types, tests and results on specimens which were artificially damaged have been performed and analyzed.

Keywords: NDT, correlation analysis, image processing, damage, inspection

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: Babar Sultan, Kiran Sultan, Waseem Khan, Ijaz Mansoor Qureshi

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In this paper, a novel idea for the performance enhancement of secondary network is proposed for Underlay Cognitive Radio Networks (CRNs). In Underlay CRNs, primary users (PUs) impose strict interference constraints on the secondary users (SUs). The proposed scheme is based on Artificial Bee Colony (ABC) optimization for relay selection and power allocation to handle the highlighted primary challenge of Underlay CRNs. ABC is a simple, population-based optimization algorithm which attains global optimum solution by combining local search methods (Employed and Onlooker Bees) and global search methods (Scout Bees). The proposed two-phase relay selection and power allocation algorithm aims to maximize the signal-to-noise ratio (SNR) at the destination while operating in an underlying mode. The proposed algorithm has less computational complexity and its performance is verified through simulation results for a different number of potential relays, different interference threshold levels and different transmit power thresholds for the selected relays.

Keywords: artificial bee colony, underlay spectrum sharing, cognitive radio networks, amplify-and-forward

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Authors: Aleksey Fedorov

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Building a scalable platform for quantum computing remains one of the most challenging tasks in quantum science and technologies. However, the implementation of most important quantum operations with qubits (quantum analogues of classical bits), such as multiqubit Toffoli gate, requires either a polynomial number of operation or a linear number of operations with the use of ancilla qubits. Therefore, the reduction of the number of operations in the presence of scalability is a crucial goal in quantum information processing. One of the most elegant ideas in this direction is to use qudits (multilevel systems) instead of qubits and rely on additional levels of qudits instead of ancillas. Although some of the already obtained results demonstrate a reduction of the number of operation, they suffer from high complexity and/or of the absence of scalability. We show a strong reduction of the number of operations for the realization of the Toffoli gate by using qudits for a scalable multi-qudit processor. This is done on the basis of a general relation between the dimensionality of qudits and their topology of connections, that we derived.

Keywords: quantum computing, qudits, Toffoli gates, gate decomposition

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Authors: John Davidson, Matteo Castelletti, Ismael Torres, Victor Terente, Jamie Irvine, Sylvie Raymackers

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The current industry approach to pile driving predictions consists of developing a model of the hammer-pile-soil system which simulates the relationship between soil resistance to driving (SRD) and blow counts (or pile penetration per blow). The SRD methods traditionally used are broadly based on static pile capacity calculations. The SRD is used in combination with the one-dimensional wave equation model to indicate the anticipated blowcounts with depth for specific hammer energy settings. This approach has predominantly been calibrated on relatively long slender piles used in the oil and gas industry but is now being extended to allow calculations to be undertaken for relatively short rigid large diameter monopile foundations. This paper evaluates the accuracy of current industry practice when applied to a site where large diameter monopiles were installed in predominantly stiff fissured clay. Actual geotechnical and pile installation data, including pile driving records and signal matching analysis (based upon pile driving monitoring techniques), were used for the assessment on the case study site.

Keywords: driven piles, fissured clay, London clay, monopiles, offshore foundations

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Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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Authors: Jerzy Merkisz, Piotr Lijewski, Pawel Fuc, Maciej Siedlecki, Andrzej Ziolkowski, Sylwester Weymann

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The paper discusses the problem of load transport using farm tractors and road tractor units. This type of carriage of goods is often done with farm vehicles. The tests were performed with the PEMS equipment (Portable Emission Measurement System) under actual traffic conditions. The vehicles carried a load of 20000 kg. This research method is one of the most desired because it provides reliable information on the actual vehicle emissions and fuel consumption (carbon balance method). For the tests, a route was selected that simulated a trip from a small town to a food-processing facility located in a city. The analysis of the obtained results gave a clear answer as to what vehicles need to be used for the carriage of this type of cargo in terms of exhaust emissions and fuel consumption.

Keywords: emission, transport, fuel consumption, PEMS

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Authors: Ružica Tomičić, Zorica Tomičić, Peter Raspor

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An abundant growth of unwanted yeasts in food processing plants can lead to problems in quality and safety with significant financial losses. Candida and Pichia are the genera mainly involved in spoilage of products in the food and beverage industry. These contaminating microorganisms can form biofilms on food contact surfaces, being difficult to eradicate, increasing the probability of microbial survival and further dissemination during food processing. It is well known that biofilms are more resistant to antimicrobial agents compared to planktonic cells and this makes them difficult to eliminate. Among the strategies used to overcome resistance to antifungal drugs and preservatives, the use of natural substances such as plant extracts has shown particular promise, and many natural substances have been found to exhibit antifungal properties. This study aimed to investigated the impact of growth medium (Malt Extract broth (MEB) or Yeast Peptone Dextrose (YPD) broth) and temperatures (7°C, 37°C, 43°C for Candida strains and 7°C, 27°C, 32°C for Pichia strains) on the adhesion of Candida spp. and Pichia spp. to stainless steel (AISI 304) discs with different degrees of surface roughness (Ra = 25.20 – 961.9 nm), a material commonly used in the food industry. We also evaluated the antifungal and antiadhesion activity of plant extracts such as Humulus lupulus, Alpinia katsumadai and Evodia rutaecarpa against C. albicans, C glabrata and P. membranifaciens and investigated whether these plant extracts can interfere with biofilm formation. The adhesion was assessed by the crystal violet staining method, while the broth microdilution method CLSI M27-A3 was used to determine the minimum inhibitory concentration (MIC) of plant extracts. Our results indicated that the nutrient content of the medium significantly influenced the amount of adhered cells of the tested yeasts. The growth medium which resulted in a higher adhesion of C. albicans and C. glabrata was MEB, while for C. parapsilosis and C. krusei was YPD. In the case of P. pijperi and P. membranifaciens, YPD broth was more effective in promoting adhesion than MEB. Regarding the effect of temperature, C. albicans strain adhered to stainless steel surfaces in significantly higher level at a temperature of 43°C, while on the other hand C. glabrata, C. parapsilosis and C. krusei showed a different behavior with significantly higher adhesion at 37°C than at 7°C and 43°C. Further, the adherence ability of Pichia strains was highest at 27°C. Based on the MIC values, all plant extracts exerted significant antifungal effects with MIC values ranged from 100 to 400 μg/mL. It was observed that biofilm of C. glabrata were more resistance to plant extracts as compared to C. albicans. However, extracts of A. katsumadai and E. rutaecarpa promoted the growth and development of the preformed biofilm of P. membranifaciens. Thus, the knowledge of how these microorganisms adhere and which factors affect this phenomenon is of great importance in order to avoid their colonization on food contact surfaces.

Keywords: adhesion, Candida spp., Pichia spp., plant extracts

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Authors: Nhat Linh Ho, Thanh-Phong Dao, Shyh-Chour Huang, Hieu Giang Le

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This paper presents a design and optimization for a compliant gripper. The gripper is constructed based on the concept of compliant mechanism with flexure hinge. A passive force regulation mechanism is presented to control the grasping force a micro-sized object instead of using a sensor force. The force regulation mechanism is designed using the planar springs. The gripper is expected to obtain a large range of displacement to handle various sized objects. First of all, the statics and dynamics of the gripper are investigated by using the finite element analysis in ANSYS software. And then, the design parameters of the gripper are optimized via Taguchi method. An orthogonal array L₉ is used to establish an experimental matrix. Subsequently, the signal to noise ratio is analyzed to find the optimal solution. Finally, the response surface methodology is employed to model the relationship between the design parameters and the output displacement of the gripper. The design of experiment method is then used to analyze the sensitivity so as to determine the effect of each parameter on the displacement. The results showed that the compliant gripper can move with a large displacement of 213.51 mm and the force regulation mechanism is expected to be used for high precision positioning systems.

Keywords: flexure hinge, compliant mechanism, compliant gripper, force regulation mechanism, Taguchi method, response surface methodology, design of experiment

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Authors: Charlotte Entwistle, Ryan Boyd

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Recent developments in information retrieval techniques and natural language processing have allowed for greater exploration of psychological and social processes. Linguistic analysis methods for understanding behaviour have provided useful insights within the field of mental health. One area within mental health that has received little attention though, is borderline personality disorder (BPD). BPD is a common mental health disorder characterised by instability of interpersonal relationships, self-image and affect. It also manifests through maladaptive behaviours, such as impulsivity and self-harm. Examination of language patterns associated with BPD could allow for a greater understanding of the disorder and its links to maladaptive thoughts and behaviours. Language analysis methods could also be used in a predictive way, such as by identifying indicators of BPD or predicting maladaptive thoughts, emotions and behaviours. Additionally, associations that are uncovered between language and maladaptive thoughts and behaviours could then be applied at a more general level. This study explores linguistic characteristics of BPD, and their links to maladaptive thoughts and behaviours, through the analysis of social media data. Data were collected from a large corpus of posts from the publicly available social media platform Reddit, namely, from the ‘r/BPD’ subreddit whereby people identify as having BPD. Data were collected using the Python Reddit API Wrapper and included all users which had posted within the BPD subreddit. All posts were manually inspected to ensure that they were not posted by someone who clearly did not have BPD, such as people posting about a loved one with BPD. These users were then tracked across all other subreddits of which they had posted in and data from these subreddits were also collected. Additionally, data were collected from a random control group of Reddit users. Disorder-relevant behaviours, such as self-harming or aggression-related behaviours, outlined within Reddit posts were coded to by expert raters. All posts and comments were aggregated by user and split by subreddit. Language data were then analysed using the Linguistic Inquiry and Word Count (LIWC) 2015 software. LIWC is a text analysis program that identifies and categorises words based on linguistic and paralinguistic dimensions, psychological constructs and personal concern categories. Statistical analyses of linguistic features could then be conducted. Findings revealed distinct linguistic features associated with BPD, based on Reddit posts, which differentiated these users from a control group. Language patterns were also found to be associated with the occurrence of maladaptive thoughts and behaviours. Thus, this study demonstrates that there are indeed linguistic markers of BPD present on social media. It also implies that language could be predictive of maladaptive thoughts and behaviours associated with BPD. These findings are of importance as they suggest potential for clinical interventions to be provided based on the language of people with BPD to try to reduce the likelihood of maladaptive thoughts and behaviours occurring. For example, by social media tracking or engaging people with BPD in expressive writing therapy. Overall, this study has provided a greater understanding of the disorder and how it manifests through language and behaviour.

Keywords: behaviour analysis, borderline personality disorder, natural language processing, social media data

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Authors: Thu Le Thi Bao

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Industrial parks have both active roles in promoting economic development and source of appearance of boarding houses and slums in the adjacent area, lacking infrastructure, causing many social evils. The context of the recent pandemic and climate change on a global scale pose issues that need to be resolved for sustainable development. Ho Chi Minh City aims to develop housing for migrant workers to stabilize human resources and, at the same time, solve problems of social evils caused by poor living conditions. The paper focuses on the content of renovating existing industrial parks and worker accommodation in Ho Chi Minh City to propose appropriate models, contributing to the goal of urban embellishment and solutions for industrial parks to adapt to abnormal impact conditions such as pandemics, climate change, crises.

Keywords: industrial park, social housing, accommodation, distribution center

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Authors: Diya Alsafadi, Fawwaz Khalili, Mohammad W. Amer

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Butanol is an important industrial solvent and potentially a better liquid transportation biofuel than ethanol. The cost of feedstock is one key problem associated with the biobutanol production. Date palm is sugar-rich fruit and highly abundant. Thousands of tons of date wastes that generated from date processing industries are thrown away each year and imposing serious environmental problems. To exploit the utilization of renewable biomass feedstock, date palm waste was utilized for butanol production by Clostridium acetobutylicum DSM 1731. Fermentation conditions were optimized by investigating several parameters that affect the production of butanol such as temperature, substrate concentration and pH. The highest butanol yield (1.0 g/L) and acetone, butanol, and ethanol (ABE) content (1.3 g/L) were achieved at 20 g/L date waste, pH 5.0 and 37 °C. These results suggest that date palm waste can be used for biobutanol production.

Keywords: biofuel, acetone-butanol-ethanol fermentation, date palm waste, Clostridium acetobutylicum

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Authors: Abhigna Bhatt, Arnab Banerjee

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A periodic system with only a single coupling degree of freedom is called a monocoupled system. Monocoupled systems with mechanisms like mass in the mass system generates effective negative mass, mass connected with rigid links generates inertial amplification, and spring-mass connected with a rigid link generateseffective negative stiffness. In this paper, the representative unit cell is introduced, considering all three mechanisms combined. Further, the dynamic stiffness matrix of the unit cell is constructed, and the dispersion relation is obtained by applying the Bloch theorem. The frequency response function is also calculated for the finite length of periodic unit cells. Moreover, the input displacement signal is given to the finite length of periodic structure and using inverse Fourier transform to visualize the wave propagation in the time domain. This visualization explains the sudden attenuation in metamaterial due to energy dissipation by an embedded resonator at the resonance frequency. The visualization created for wave propagation is found necessary to understand the insights of physics behind the attenuation characteristics of the system.

Keywords: mono coupled system, negative effective mass, negative effective stiffness, inertial amplifier, fourier transform

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Authors: Yung-Shan Lu, Chia-Fone Lee, Shang-Hsuan Li, Chien-Hao Liu

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Recently, various bioelectronic devices have been developed for neurologic disease treatments via electro-stimulations such as cochlear implants and retinal prosthesis. Since the electric signal needs electrodes to be transmitted to an organism, electrodes play an important role of stimulations. The materials of stimulation electrodes affect the efficiency of the delivered currents. The higher the efficiency of the electrodes, the lower the threshold current can be used to stimulate the organism which minimizes the potential damages to the adjacent tissues. In this study, we proposed a biocompatible composite electrode composed of high-charge-capacity iridium oxide (IrOₓ) film for a bone-guide extra-cochlear implant. IrOₓ was exploited to decrease the threshold current due to its high capacitance and low impedance. The IrOₓ electrode was fabricated via microelectromechanical systems (MEMS) photolithography and examined with in-vivo tests with guinea pigs. Based on the measured responses of brain waves to sound, the results demonstrated that IrOₓ electrodes have a lower threshold current compared with the Platinum (Pt) electrodes. The research results are expected to be beneficial for implantable and biocompatible electrodes for electrical stimulations.

Keywords: cochlear implants, electrode, electrical stimulation, iridium oxide

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Authors: Amir Azaron

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In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

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Authors: Iris Käppler, Paul Matthäi, Chokri Cherif

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In the scope of application of technical textiles, Non-Crimp Fabrics are increasingly used. In general, NCF exhibit excellent load bearing properties, but caused by the manufacturing process, there are some remaining disadvantages which have to be reduced. Regarding to this, a novel technique of processing NCF was developed substituting the binding-thread by an adhesive. This stitch-free method requires new manufacturing concept as well as new basic methods to prove adhesion of glue at fibres and textiles. To improve adhesion properties and the wettability of carbon-fibres by the adhesive, oxyfluorination was used. The modification of carbon-fibres by oxyfluorination was investigated via scanning electron microscope, X-ray photo electron spectroscopy and single fibre tensiometry. Special tensile tests were developed to determine the maximum force required for detachment.

Keywords: non-crimp fabric, adhesive, stitch-free, high-performance fibre

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Authors: Denis Özdemir, Max Senges

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There are many examples of AI-supported apps for better health and wellbeing. Generally, these applications help people to achieve their goals based on scientific research and input data. Still, they do not always explain how those three are related, e.g. by making implicit assumptions about goals that hold for many but not for all. We present a seven-step method for designing health and wellbeing AIs considering goal setting, measurable results, real-time indicators, analytics, visual representations, communication, and feedback. It can help engineers as guidance in developing apps, recommendation algorithms, and interfaces that support humans in their decision-making without patronization. To illustrate the method, we create a recommender AI for tiny wellbeing habits and run a small case study, including a survey. From the results, we infer how people perceive the relationship between them and the AI and to what extent it helps them to achieve their goals. We review our seven-step engineering method and suggest modifications for the next iteration.

Keywords: recommender systems, natural language processing, health apps, engineering methods

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Authors: Cheng-yu Hsieh, Bo Zhang, Ahmed Hambaba

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Stock market prediction has long been an area of interest for both expert analysts and investors, driven by its complexity and the noisy, volatile conditions it operates under. This research examines the efficacy of combining the Patch Time Series Transformer (PatchTST) with wavelet transforms, specifically focusing on Haar and Daubechies wavelets, in forecasting the adjusted closing price of the S&P 500 index for the following day. By comparing the performance of the augmented PatchTST models with traditional predictive models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, this study highlights significant enhancements in prediction accuracy. The integration of the Daubechies wavelet with PatchTST notably excels, surpassing other configurations and conventional models in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE). The success of the PatchTST model paired with Daubechies wavelet is attributed to its superior capability in extracting detailed signal information and eliminating irrelevant noise, thus proving to be an effective approach for financial time series forecasting.

Keywords: deep learning, financial forecasting, stock market prediction, patch time series transformer, wavelet transform

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Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

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This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: image forensics, computer graphics, classification, deep learning, convolutional neural networks

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC

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Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

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Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

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Authors: Fidiana Suwitho

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Research and community service is one of important lecturer assignment in Indonesia. This article was made to meet those needs by assisting home industry entrepreneurs of various chips in Banyuwangi. Community service in this scheme are intended to increase the revenue of craftsmen of chips by improving value added of chips through food engineering technology. Ibu Anisa has produced various kinds of chips that are breadfruit chips, banana chips, yam chips, and cassava chips. In business development, Ibu Anisa facing various problems both in terms of production and management aspects. The process of production and management and marketing are still conventional so that increased demand cannot be offset by production capacity. A researcher team of STIESIA has assist partners in the processing stage, from manually to the technologically. This activity has a positive impact to However, this process has not been reached on sustainable marketing aspect, which is where the partners are still difficult to reach a wider market because of limited access.

Keywords: food engineering technology, value added of chips, community service

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Ting-Ting Wen, Jung-Ruey Tsai

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This paper reports a method for the replication of micro-scale structures. By using electromagnetic force-assisted imprinting system with magnetic soft stamp written square-microlens cavity, a photopolymer square-microlens structures can be rapidly fabricated. Under the proper processing conditions, the polymeric square-microlens structures with feature size of width 100.3um and height 15.2um across a large area can be successfully fabricated. Scanning electron microscopy (SEM) and surface profiler observations confirm that the micro-scale polymer structures are produced without defects or distortion and with good pattern fidelity over a 60x60mm2 area. This technique shows great potential for the efficient replication of the micro-scale structure array at room temperature and with high productivity and low cost.

Keywords: square-microlens structures, electromagnetic force-assisted imprinting, magnetic soft stamp

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Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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Authors: Tuji Jemal Ahmed, Abdi Mohammed, Geremew Geidare Kailo

Abstract:

Food security, foodborne illness, and food safety are critical issues that affect the East Harerghe region of Oromia, Ethiopia. Despite the region's potential for agriculture, food insecurity remains a significant problem, with many households experiencing chronic hunger and malnutrition. The region also experiences high rates of foodborne illnesses, including cholera, typhoid, and diarrhea, which are caused by poor hygiene and sanitation practices. Additionally, food safety is a significant challenge, particularly in rural areas, where there is a lack of infrastructure, inadequate food storage facilities, and limited access to information about food safety. There are several factors that contribute to the current situation in the East Harerghe region; firstly, the region is susceptible to natural disasters, for instance, drought, which affects crop yields and livestock production. Secondly, the region also experiences poor infrastructure, which affects the storage and transportation of food, particularly in rural areas. Thirdly, there is a lack of awareness and knowledge on good hygiene and sanitation practices, specifically during food handling, processing, and storage. Fourthly, unitability due to conflict and other forms of land degradation exacerbates food insecurity and malnutrition. Finally, limited access to financial resources and markets commonly affects smallholder farmers by their ability to produce and sell food. To address the current situation in that area, several potential solutions can be implemented; investment in infrastructure is necessary, especially in rural areas, to improve the storage and transportation of food. Education and awareness programs on good hygiene and sanitation practices should target local communities, smallholder farmers, and food vendors. Financial resources and markets should be made more accessible to smallholder farmers, particularly through the provision of credit and improved access to markets. Addressing the underlying causes of conflict and promoting peaceful coexistence can help to reduce displacement and loss of livelihoods. Finally, the enforcement of food safety regulations and the implementation of standards for food processing and storage facilities are necessary to ensure food safety. In conclusion, addressing the challenges of food security, foodborne illness, and food safety in the East Harerghe region requires a coordinated effort from various stakeholders, including the government, non-governmental organizations, and local communities. By implementing the solutions outlined above, the region can improve its food security, prevent foodborne illnesses, and keep food safe for its population. Eventually, building the resilience of communities to shocks such as droughts, floods, and conflict is necessary to ensure long-term food security in the region.

Keywords: foodborne illness, food handling, food safety, food security

Procedia PDF Downloads 73

Authors: Tahseen Saad, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

Abstract:

A new concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. To control the coordination problem, which depends on offset selection and to estimate uniform delay based on the offset choice in a traffic signal network. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and are compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show new model minimizes the total uniform delay to almost half compared to conventional models. The mathematical objective function is robust. The algorithm convergence time is fast.

Keywords: area traffic control, traffic flow, differential evolution, sinusoidal periodic function, uniform delay, offset variable

Procedia PDF Downloads 256

Authors: A. Rahaf, S. Liyakathunsia

Abstract:

In today’s world, unprecedented operational pressure is faced by banks that test the efficiency, effectiveness, and agility of their business processes. In a typical banking process, a person’s authorization is usually based on his signature on most all of the transactions. Signature verification is considered as one of the highly significant information needed for any bank document processing. Banks usually use Signature Verification to authenticate the identity of individuals. In this paper, a business process model has been proposed in order to increase the quality of the verification process and to reduce time and needed resources. In order to understand the current process, a survey has been conducted and distributed among bank employees. After analyzing the survey, a process model has been created using Bizagi modeler which helps in simulating the process after assigning time and cost of it. The outcomes show that the automation of signature verification process is highly recommended for a banking business process.

Keywords: business process management, process modeling, quality, Signature Verification

Procedia PDF Downloads 399

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud Ccomputing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 452