Search results for: modular wound rotor synchronous machine

Authors: Jennifer Leach, Umashanger Thayasivam

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The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, though, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate people. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease this advancement. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent data, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which testing split and technique would lead to the most optimal results.

Keywords: data science, fraud detection, machine learning, supervised learning

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Authors: M. Khaledi Pour, P. Akbartehrani, M. Amini, M. Khani, M. Mohajeri Tehrani, R. Radi, B. Shokri

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Diabetic Foot Ulcer (DFU) is one of the costly severe complications of diabetes. Neuropathy and Peripheral Arterial Disease (PAD) due to diabetes are significant causes of this complication. In 10 years the patients with DFUs are twice as likely to die as patients without DFUs. Cold Atmospheric Plasma (CAP) is a promising tool for medical purposes. CAP generate reactive species at room temperature and are effective in killing bacteria and fibroblast proliferation. These CAP-based tools produce NO, which has bactericidal and angiogenesis properties. It also showed promising effects in the DFUs surface reduction and the time to wound closure. In this paper, we evaluated the effect of the Argon Plasma Jet (APJ) on the healing process of the Wagner Grade 2 DFUs in a randomized clinical trial. The 20 kHz sinusoidal voltage frequency derives the APJ. Patients (n=20) were randomly double-blinded assigned into two groups. These groups receive the standard care (SC, n=10) and the standard care with APJ treatment (SC+APJ, n=10) for five sessions in four weeks. The results showed that the APJ treatment along standard care could reduce the wound surface by 20 percent more than the standard care. Also, It showed a more influential role in controlling wound infection.

Keywords: argon plasma jet, cold atmospheric plasma, diabetes, diabetic foot ulcer

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Authors: Yi-Fei Yang, Nai-Bao He, Shao-Bang Xing

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This study investigates the permanent magnet synchronous linear motor (PMSLM) chaotic motion under the specific physical parameters, the stability and the security of motor-driven system will be unavoidably influenced. Therefore, it is really necessary to investigate the methods of controlling or suppressing chaos in PMSLM. Firstly, we derive a chaotic model of PMSLM in the closed-loop system. Secondly, in order to realize the local asymptotic stabilization of the mechanical subsystem and the global stabilization of the motor-driven system including electrical subsystem, we propose an improved uniting control lyapunov functions by introducing backstepping approach. Finally, an illustrated example is also given to show the electiveness of the obtained results.

Keywords: linear motor, lyapunov functions, chao control, hybrid controller

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Authors: Patrícia Severino, Luciana Nalone, Daniele Martins, Marco Chaud, Classius Ferreira, Cristiane Bani, Ricardo Albuquerque

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Hydrogels produced with polymers have been used in the development of dressings for wound treatment and tissue revitalization. Our study on polymer nanocomposites containing silver nanoparticles shows antimicrobial activity and applications in wound healing. The effects are linked with the slow oxidation and Ag⁺ liberation to the biological environment. Furthermore, bacterial cell membrane penetration and metabolic disruption through cell cycle disarrangement also contribute to microbial cell death. The silver antimicrobial activity has been known for many years, and previous reports show that low silver concentrations are safe for human use. This work aims to develop a hydrogel using natural polymers (sodium alginate and gelatin) combined with silver nanoparticles for wound healing and with antimicrobial properties in cutaneous lesions. The hydrogel development utilized different sodium alginate and gelatin proportions (20:80, 50:50 and 80:20). The silver nanoparticles incorporation was evaluated at the concentrations of 1.0, 2.0 and 4.0 mM. The physico-chemical properties of the formulation were evaluated using ultraviolet-visible (UV-Vis) absorption spectroscopy, Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), and thermogravimetric (TG) analysis. The morphological characterization was made using transmission electron microscopy (TEM). Human fibroblast (L2929) viability assay was performed with a minimum inhibitory concentration (MIC) assessment as well as an in vivo cicatrizant test. The results suggested that sodium alginate and gelatin in the (80:20) proportion with 4 mM of AgNO₃ in the (UV-Vis) exhibited a better hydrogel formulation. The nanoparticle absorption spectra of this analysis showed a maximum band around 430 - 450 nm, which suggests a spheroidal form. The TG curve exhibited two weight loss events. DSC indicated one endothermic peak at 230-250 °C, due to sample fusion. The polymers acted as stabilizers of a nanoparticle, defining their size and shape. Human fibroblast viability assay L929 gave 105 % cell viability with a negative control, while gelatin presented 96% viability, alginate: gelatin (80:20) 96.66 %, and alginate 100.33 % viability. The sodium alginate:gelatin (80:20) exhibited significant antimicrobial activity, with minimal bacterial growth at a ratio of 1.06 mg.mL⁻¹ in Pseudomonas aeruginosa and 0.53 mg.mL⁻¹ in Staphylococcus aureus. The in vivo results showed a significant reduction in wound surface area. On the seventh day, the hydrogel-nanoparticle formulation reduced the total area of injury by 81.14 %, while control reached a 45.66 % reduction. The results suggest that silver-hydrogel nanoformulation exhibits potential for wound dressing therapeutics.

Keywords: nanocomposite, wound healing, hydrogel, silver nanoparticle

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Authors: Estelle Arbellay, Lori D. Daniels, Shawn D. Mansfield, Alice S. Chang

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Mountain pine beetle (MPB) outbreaks are currently devastating lodgepole pine forests in western North America, which are also widely disturbed by frequent wildfires. Both MPB and fire can leave scars on lodgepole pine trees, thereby diminishing their commercial value and possibly compromising their utilization in solid wood products. In order to fully exploit the affected resource, it is crucial to understand how wounding from these two disturbance agents impact wood properties. Moreover, previous research on lodgepole pine has focused solely on sound wood and stained wood resulting from the MPB-transmitted blue fungi. By means of a quantitative multi-proxy approach, we tested the hypotheses that (i) wounding (of either MPB or fire origin) caused significant changes in wood properties of lodgepole pine and that (ii) MPB-induced wound effects could differ from those induced by fire in type and magnitude. Pith-to-bark strips were extracted from 30 MPB scars and 30 fire scars. Strips were cut immediately adjacent to the wound margin and encompassed 12 rings from normal wood formed prior to wounding and 12 rings from wound wood formed after wounding. Wood properties evaluated within this 24-year window included ring width, relative wood density, cellulose crystallinity, fibre dimensions, and carbon and nitrogen concentrations. Methods used to measure these proxies at a (sub-)annual resolution included X-ray densitometry, X-ray diffraction, fibre quality analysis, and elemental analysis. Results showed a substantial growth release in wound wood compared to normal wood, as both earlywood and latewood width increased over a decade following wounding. Wound wood was also shown to have a significantly different latewood density than normal wood 4 years after wounding. Latewood density decreased in MPB scars while the opposite was true in fire scars. By contrast, earlywood density was presented only minor variations following wounding. Cellulose crystallinity decreased in wound wood compared to normal wood, being especially diminished in MPB scars the first year after wounding. Fibre dimensions also decreased following wounding. However, carbon and nitrogen concentrations did not substantially differ between wound wood and normal wood. Nevertheless, insect-feeding and fire-heating wounding were shown to significantly alter most wood properties of lodgepole pine, as demonstrated by the existence of several morphological anomalies in wound wood. MPB and fire generally elicited similar anomalies, with the major exception of latewood density. In addition to providing quantitative criteria for differentiating between biotic (MPB) and abiotic (fire) disturbances, this study provides the wood industry with fundamental information on the physiological response of lodgepole pine to wounding in order to evaluate the utilization of scarred trees in solid wood products.

Keywords: elemental analysis, fibre quality analysis, lodgepole pine, wood properties, wounding, X-ray densitometry, X-ray diffraction

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Authors: Chee Sun Won

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This paper presents the size reduction of images for machine-to-machine communications. Here, the salient image regions to be preserved include the image patches of the key-points such as corners and blobs. Based on a saliency image map from the key-points and their image patches, an axis-aligned grid-size optimization is proposed for the reduction of image size. To increase the size-reduction efficiency the aspect ratio constraint is relaxed in the constraint optimization framework. The proposed method yields higher matching accuracy after the size reduction than the conventional content-aware image size-reduction methods.

Keywords: image compression, image matching, key-point detection and description, machine-to-machine communication

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Authors: Sebastian Kehne, Alexander Epple, Werner Herfs

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A new method for optimal selection of components for multi-axes forward-feed drive systems is proposed in which the choice of motors, gear boxes and ball screw drives is optimized. Essential is here the synchronization of electrical and mechanical frequency behavior of all axes because even advanced controls (like H∞-controls) can only control a small part of the mechanical modes – namely only those of observable and controllable states whose value can be derived from the positions of extern linear length measurement systems and/or rotary encoders on the motor or gear box shafts. Further problems are the unknown processing forces like cutting forces in machine tools during normal operation which make the estimation and control via an observer even more difficult. To start with, the open source Modelica Feed Drive Library which was developed at the Laboratory for Machine Tools, and Production Engineering (WZL) is extended from one axis design to the multi axes design. It is capable to simulate the mechanical, electrical and thermal behavior of permanent magnet synchronous machines with inverters, different gear boxes and ball screw drives in a mechanical system. To keep the calculation time down analytical equations are used for field and torque producing equivalent circuit, heat dissipation and mechanical torque at the shaft. As a first step, a small machine tool with a working area of 635 x 315 x 420 mm is taken apart, and the mechanical transfer behavior is measured with an impulse hammer and acceleration sensors. With the frequency transfer functions, a mechanical finite element model is built up which is reduced with substructure coupling to a mass-damper system which models the most important modes of the axes. The model is modelled with Modelica Feed Drive Library and validated by further relative measurements between machine table and spindle holder with a piezo actor and acceleration sensors. In a next step, the choice of possible components in motor catalogues is limited by derived analytical formulas which are based on well-known metrics to gain effective power and torque of the components. The simulation in Modelica is run with different permanent magnet synchronous motors, gear boxes and ball screw drives from different suppliers. To speed up the optimization different black-box optimization methods (Surrogate-based, gradient-based and evolutionary) are tested on the case. The objective that was chosen is to minimize the integral of the deviations if a step is given on the position controls of the different axes. Small values are good measures for a high dynamic axes. In each iteration (evaluation of one set of components) the control variables are adjusted automatically to have an overshoot less than 1%. It is obtained that the order of the components in optimization problem has a deep impact on the speed of the black-box optimization. An approach to do efficient black-box optimization for multi-axes design is presented in the last part. The authors would like to thank the German Research Foundation DFG for financial support of the project “Optimierung des mechatronischen Entwurfs von mehrachsigen Antriebssystemen (HE 5386/14-1 | 6954/4-1)” (English: Optimization of the Mechatronic Design of Multi-Axes Drive Systems).

Keywords: ball screw drive design, discrete optimization, forward feed drives, gear box design, linear drives, machine tools, motor design, multi-axes design

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Authors: Kirti Gosavi, Anita Bhole

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The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.

Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor

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Authors: Kyle De Freitas, Margaret Bernard

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Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

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Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

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Authors: Chivon Choeung, Heng Tang, Panha Soth, Vichet Huy

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This paper presents a robust control strategy for a single-phase DC-AC inverter with an output LC-filter. An all-pass filter is utilized to create an artificial β-signal so that the proposed controller can be simply used in dq-synchronous frame. The proposed robust controller utilizes a state feedback control with integral action in the dq-synchronous frame. A linear matrix inequality-based optimization scheme is used to determine stabilizing gains of the controllers to maximize the convergence rate to steady state in the presence of uncertainties. The uncertainties of the system are described as the potential variation range of the inductance and resistance in the LC-filter.

Keywords: single-phase inverter, linear matrix inequality, robust control, all-pass filter

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

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Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

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Authors: V. Srikanth, K. Balasubramanian, Rajath R. Bhat, A. S. Arjun, Nandhu Venugopal, Ananthu Unnikrishnan

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Indirect vector control is known to produce high performance in Permanent Magnet Synchronous Motor (PMSM) drives by decoupling flux and torque producing current components of stator current. The most commonly used controller or the vector control of AC motor is Proportional-Integral (P-I) controller. However, the P-I controller has some disadvantages such as high starting overshoot, sensitivity to controller gains and slower response to sudden disturbance. Therefore, the Integral-Proportional controller for PMSM drives to overcome the disadvantages of the P-I controller. Simulations results are presented and analyzed for both controllers and it is observed that Integral-Proportional (I-P) controllers give better responses than the traditional P-I controllers.

Keywords: PMSM, FOC, PI controller, IP controller

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Authors: Arman Kishan, Mark Haft, Steve Li, Duc Nguyen, Dawn Laporte

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Objective: Patients with Type 2 diabetes (T2DM) often face higher postoperative complication rates. Limited data exist on outcomes in T2DM patients undergoing carpal tunnel release (CTR). This study aims to compare complication rates between endoscopic CTR (ECTR) and open CTR (OCTR) in patients with T2DM. Methods: This was a retrospective cohort study using the TriNetX database of 56741 patients with T2DM undergoing ECTR (N= 14,949) or OCTR (N= 41,792). Demographic data, medical comorbidities, and complication rates were analyzed. We used multivariable analysis to identify differences in postoperative complication rates between the two treatment methods in patients with T2DM. Results: Patients with T2DM undergoing ECTR had a significantly lower incidence of 90-day wound infection (p < 0.001), 90-day wound dehiscence (p < 0.001), and nerve injury (p < 0.001) when compared to patients who underwent OCTR. After matching, there was a significantly higher number of T2DM patients undergoing ECTR who had peripheral vascular disease (p = 0.045) and hypertension (p = 0.020) when compared to the OCTR group. These patients also had a lower incidence of fluid and electrolyte disorders (p = 0.002) and chronic blood loss anemia (p = 0.025). Conclusion: ECTR presents a superior choice for T2DM patients undergoing CTR, yielding significantly lower rates of wound infection, wound dehiscence, and nerve injury within 90 days post-surgery—reducing the risk by 31%, 48%, and 59%, respectively. These findings support the adoption of ECTR as the preferred method in this patient population, potentially leading to improved postoperative outcomes.

Keywords: endoscopic treatment of carpal tunnel syndrome, open treatment of carpal tunnel syndrome, carpal tunnel syndrome, postoperative complications in patients with diabetes mellitus

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Authors: Janet Kaningen, Richard N. Kaningen, Jonas Kaningen

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This paper aims to discover the best ways to improve production efficiency, cost efficiency, community cohesion, and long-term sustainability in Ghana's housing delivery. Advanced Construction Technologies (ACTs) are set to become the sustainable mainstay of the construction industry due to the demand for innovative housing solutions. Advances in material science, building component production, and assembly technologies are leading to the development of next-generation materials such as polymeric-fiber-based products, light-metal alloys, and eco-materials. Modular housing construction has become more efficient and cost-effective than traditional building methods and is becoming increasingly popular for commercial, industrial, and residential projects. Effective project management and logistics will be imperative in the future speed and cost of modular construction housing.

Keywords: technology blending, sustainability, housing, Ghana

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Authors: R. Suresh, C. B. Singh, A. K. Sarda

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Background: Over the decades, several surgical techniques have been developed to treat anal fistulas with variable success rates and complications. Large amount of work has been done in radiofrequency excision of the fistula for several years but no work has been done for ablating the tract. Therefore one can consider for obliteration ofanal fistula by Radiofrequency ablation (RFA). Material and Methods: A randomized controlled clinical trial was conducted at Lok Nayak Hospital, where a total of 40 patients were enrolled in the study and they were randomly assigned to Group I (fistulectomy)(n=20) and Group II (RFA) (n=20). Aim of the study was to compare the efficacy of RFA of fistula versus fistulectomy in the treatment of a low anal fistula and to evaluate RFA as an effective alternative to fistulectomy with respect to time taken for wound healing as primary outcome and post-operative pain, time taken to return to work as secondary outcomes. Patients with simple low anal fistulas, single internal and external opening, not more than two secondary tracts were included. Patients with high complex fistula, fistulas communicating with cavity, fistula due to condition like tuberculosis, Crohn's, malignancy were excluded from the study. Results: Both groups were comparable with respect to age, sex ratio, type of fistula. Themean healing time was significantly shorter in group II (41.02 days) than in group I(62.68 days).The mean operative time was significantly shorter in groupII (21.40 min) than in group I(28.50 min). The mean time taken to return to work was significantly shorter in group II(8.30 days)than in group I(12.01 days).There was no significant difference in the post operative hospital stay, mean postoperative pain score, wound infection and recurrence between the two groups. Conclusion: The patients who underwent RFA of fistula had shorter wound healing time, operative time and time taken to return to work when compared to those who underwent fistulectomy and therefore RFA shows outcome comparable to fistulectomy in the treatment of low anal fistula.

Keywords: fistulectomy, low anal fistula, radio frequency ablation, wound healing

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Authors: Hansraj Bookun, Angela Tan, Rachel Xuan, Linheng Zhao, Kejia Wang, Animesh Singla, David Kim, Christopher Loupos

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Introduction: Incisional wound complications in vascular surgery patients represent a significant clinical and econometric burden of morbidity and mortality. The objective of this study was to trial the feasibility of applying the Prevena negative pressure incision management system as a routine dressing in patients who had undergone arterial surgery. Conventionally, Prevena has been applied to groin incisions, but this study features applications on multiple wound sites such as the thigh or major amputation stumps. Method: This was a cross-sectional observational, single-centre case series of 12 patients who had undergone major vascular surgery. Their wounds were managed with the Prevena system being applied either intra-operatively or on the first post-operative day. Demographic and operative details were collated as well as the length of stay and complication rates. Results: There were 9 males (75%) with mean age of 66 years and the comorbid burden was as follows: ischaemic heart disease (92%), diabetes (42%), hypertension (100%), stage 4 or greater kidney impairment (17%) and current or ex-smoking (83%). The main indications were acute ischaemia (33%), claudication (25%), and gangrene (17%). There were single instances of an occluded popliteal artery aneurysm, diabetic foot infection, and rest pain. The majority of patients (50%) had hybrid operations with iliofemoral endarterectomies, patch arterioplasties, and further peripheral endovascular treatment. There were 4 complex arterial bypass operations and 2 major amputations. The mean length of stay was 17 ± 10 days, with a range of 4 to 35 days. A single complication, in the form of a lymphocoele, was encountered in the context of an iliofemoral endarterectomy and patch arterioplasty. This was managed conservatively. There were no deaths. Discussion: The Prevena wound management system shows that in conjunction with safe vascular surgery, absolute wound complication rates remain low and that it remains a valuable adjunct in the treatment of vasculopaths.

Keywords: wound care, negative pressure, vascular surgery, closed incision

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Authors: Victorita Radulescu

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Introduction: The sewage treatment plants, in the second stage, are formed by tanks having as main purpose the formation of the suspensions with high possible solid concentration values. The paper presents a solution to produce a rapid concentration of the slurry and sludge, having as main purpose the minimization as much as possible the size of the tanks. The solution is based on a rotor with bars, tested into two different areas of industrial activity: the remediation of the wastewater from the oil industry and, in the last year, into the mining industry. Basic Methods: It was designed, realized and tested a thickening system with vertical bars that manages to reduce sludge moisture content from 94% to 87%. The design was based on the hypothesis that the streamlines of the vortices detached from the rotor with vertical bars accelerate, under certain conditions, the sludge thickening. It is moved at the lateral sides, and in time, it became sediment. The formed vortices with the vertical axis in the viscous fluid, under the action of the lift, drag, weight, and inertia forces participate at a rapid aggregation of the particles thus accelerating the sludge concentration. Appears an interdependence between the Re number attached to the flow with vortex induced by the vertical bars and the size of the hydraulic compaction phenomenon, resulting from an accelerated process of sedimentation, therefore, a sludge thickening depending on the physic-chemical characteristics of the resulting sludge is projected the rotor's dimensions. Major findings/ Results: Based on the experimental measurements was performed the numerical simulation of the hydraulic rotor, as to assure the necessary vortices. The experimental measurements were performed to determine the optimal height and the density of the bars for the sludge thickening system, to assure the tanks dimensions as small as possible. The time thickening/settling was reduced by 24% compared to the conventional used systems. In the present, the thickeners intend to decrease the intermediate stage of water treatment, using primary and secondary settling; but they assume a quite long time, the order of 10-15 hours. By using this system, there are no intermediary steps; the thickening is done automatically when are created the vortices. Conclusions: The experimental tests were carried out in the wastewater treatment plant of the Refinery of oil from Brazi, near the city Ploiesti. The results prove its efficiency in reducing the time for compacting the sludge and the smaller humidity of the evacuated sediments. The utilization of this equipment is now extended and it is tested the mining industry, with significant results, in Lupeni mine, from the Jiu Valley.

Keywords: experimental tests, hydrodynamic modeling, rotor efficiency, wastewater treatment

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Authors: O. E. Akay, E. Güzel, M. T. Özcan

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The pepper has quite a rich variety. The development of a single harvesting machine for all kinds of peppers is a difficult research topic. By development of harvesting mechanisms, we could be able to facilitate the pepper harvesting problems. In this study, an experimental harvesting machine was designed for chili pepper. Four-bar mechanism was used for the design of the prototype harvesting machine. At the result of harvest trials, 80% of peppers were harvested and 8% foreign materials were collected. These results have provided some tips on how to apply to large-scale pepper Four-bar mechanism of the harvest machine.

Keywords: kinematic simulation, four bar linkage, harvest mechanization, pepper harvest

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Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

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Authors: İkbal Eski

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This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

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Authors: W. R. Li, J. K. Xia, R. Q. Peng, Z. Y. Guo, L. Jiang

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According to 3D magnetic circuit of the transverse flux PM linear machine, distribution law is presented, and analytical expression of axial end flux leakage is derived using numerical method. Maxwell stress tensor is used to solve detent force of mover. A 3D finite element model of the transverse flux PM machine is built to analyze the flux distribution and detent force. Experimental results of the prototype verified the validity of axial end flux leakage and detent force theoretical derivation, the research on axial end flux leakage and detent force provides a valuable reference to other types of linear machine.

Keywords: axial end flux leakage, detent force, flux distribution, transverse flux PM linear machine

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Authors: Hamza Zidoum

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This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

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Authors: M. Ridwanul Hassan, Samuel George

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Aims: Steroid injections are commonly used as a diagnostic tool or an alternative to surgical management of carpal tunnel syndrome (CTS) and are generally safe. Ischaemia is a rare complication with very few cases reported in the literature. Methods: We report a case of a 50-year-old female that presented with a necrotic wound to her left palm one month after a steroid injection into the carpal tunnel. She had a 2-year history of CTS in her left hand that was treated with six previous steroid injections in primary care during this period. The wound evolved from a blister to a necrotic ulcer which led to a painful, hollow defect in the centre of her palm. She did not report any history of trauma, nor did she have any co-morbidities. Clinical photographs were taken. Results: On examination, she had a 0.5 cmx1 cm defect in the palm of her left hand down to aponeurosis. There was purulent discharge in the wound with surrounding erythema but no spreading cellulitis. She had full function of her fingers but was very tender on movements and at rest. She was admitted for intravenous antibiotics and underwent a debridement, washout, and carpal tunnel release the next day. The defect was packed to heal by secondary intention and has now fully healed one month following her operation. Conclusions: This is an extremely rare complication of steroid injections to the carpal tunnel and may have been avoided by earlier referral for surgery rather than treatment using multiple steroid injections.

Keywords: hand surgery, complication, rare, carpal tunnel syndrome

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Authors: Muhammad Khairi bin Sulaiman

Abstract:

The utilization of Building Information Modelling (BIM) in the construction industry has provided an opportunity for designers in the Architecture, Engineering and Construction (AEC) industry to proceed from the conventional method of using manual drafting to a way that creates alternative designs quickly, produces more accurate, reliable and consistent outputs. By using BIM Software, designers can create digital content that manipulates the use of data using the parametric model of BIM. With BIM software, more alternative designs can be created quickly and design problems can be explored further to produce a better design faster than conventional design methods. Generally, BIM is used as a documentation mechanism and has not been fully explored and utilised its capabilities as a design tool. Relative to the current issue, Modular Coordination (MC) design as a sustainable design practice is encouraged since MC design will reduce material wastage through standard dimensioning, pre-fabrication, repetitive, modular construction and components. However, MC design involves a complex process of rules and dimensions. Therefore, a tool is needed to make this process easier. Since the parameters in BIM can easily be manipulated to follow MC rules and dimensioning, thus, the integration of BIM software with MC design is proposed for architects during the design stage. With this tool, there will be an improvement in acceptance and practice in the application of MC design effectively. Consequently, this study will analyse and explore the function and customization of BIM objects and the capability of BIM software to expedite the application of MC design during the design stage for architects. With this application, architects will be able to create building models and locate objects within reference modular grids that adhere to MC rules and dimensions. The parametric modeling capabilities of BIM will also act as a visual tool that will further enhance the automation of the 3-Dimensional space planning modeling process. (Method) The study will first analyze and explore the parametric modeling capabilities of rule-based BIM objects, which eventually customize a reference grid within the rules and dimensioning of MC. Eventually, the approach will further enhance the architect's overall design process and enable architects to automate complex modeling, which was nearly impossible before. A prototype using a residential quarter will be modeled. A set of reference grids guided by specific MC rules and dimensions will be used to develop a variety of space planning and configuration. With the use of the design, the tool will expedite the design process and encourage the use of MC Design in the construction industry.

Keywords: building information modeling, modular coordination, space planning, customization, BIM application, MC space planning

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Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

Abstract:

In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

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Authors: Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen

Abstract:

A few years ago, a promising morphoelastic model was developed for the simulation of contraction formation after burn injuries. Contraction can lead to a serious reduction in physical mobility, like a reduction in the range-of-motion of joints. If this is the case in a healing burn wound, then this is referred to as a contracture that needs medical intervention. The morphoelastic model consists of a set of partial differential equations describing both a chemical part and a mechanical part in dermal wound healing. These equations are solved with the numerical finite element method (FEM). In this method, many calculations are required on each of the chosen elements. In general, the more elements, the more accurate the solution. However, the number of elements increases rapidly if simulations are performed in 2D and 3D. In that case, it not only takes longer before a prediction is available, the computation also becomes more expensive. It is therefore important to investigate alternative possibilities to generate the same results, based on the input parameters only. In this study, a surrogate neural network has been designed to mimic the results of the one-dimensional morphoelastic model. The neural network generates predictions quickly, is easy to implement, and there is freedom in the choice of input and output. Because a neural network requires extensive training and a data set, it is ideal that the one-dimensional FEM code generates output quickly. These feed-forward-type neural network results are very promising. Not only can the network give faster predictions, but it also has a performance of over 99%. It reports on the relative surface area of the wound/scar, the total strain energy density, and the evolutions of the densities of the chemicals and mechanics. It is, therefore, interesting to investigate the applicability of a neural network for the two- and three-dimensional morphoelastic model for contraction after burn injuries.

Keywords: biomechanics, burns, feasibility, feed-forward NN, morphoelasticity, neural network, relative surface area wound

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Authors: Andriy Fedorenko

Abstract:

Background Early closure of the open abdomen is a priority after damage control laparotomy to prevent retraction of fascial layers and prevent hernia formation that requires definitive repair at a later stage. This substantially reduces the complications associated with ventral hernia formation for up to a year after initial surgery. TopClosure® is an innovative method that employs stress-relaxation and mechanical creep for skin stretching. Its use enables the primary closure of large abdominal wall defects and mitigates large ventral hernia formation. Materials and Methods A 7-year-old girl presented with severe blast injury. She underwent initial laparotomy in a facility within the conflict zone and was transferred in a state of septic shock to our facility for further care. Her abdominal injuries included liver lacerations, multiple perforations of the transverse colon and ileum, and a 8x16cm oblique abdominal wall defect. Further damage control laparotomy was performed with primary suture of the colon and ileum and temporary closure of the abdomen using a Bagota bag. Twelve hours later, negative pressure wound therapy (NPWT) was applied to the abdominal wound after relook laparotomy. Five days later, TopClosure® was applied to the lower part of the wound incorporating NPWT to the upper wound. Results The patient suffered leak from the colonic suture line and required relaparotomy. TopClosure® abdominal closure was achieved after every laparotomy. Conclusion TopClosure® utilizes the viscoelastic properties of the skin achieving full closure of the abdominal wall (including the fascia and skin),eliminating the need for prolonged NPWT, skin graft, and delayed ventral hernia repair surgery.

Keywords: topclosure, abdominal wall defect, hernia, damage control

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Authors: S. Yeo, M. Mathur

Abstract:

Introduction: Obesity, defined as a Body Mass Index (BMI) of more than or equal to 30kg/m, is associated with an increased risk of complications during pregnancy and delivery. During labour, obese mothers often require greater intervention and have higher rates of caesarean section. Despite a low overall rate of serious complications following caesarean section, a high BMI predisposes to a higher risk of postoperative complications. Our study, therefore, aimed to investigate the impact of antenatal obesity on adverse outcomes following caesarean section, particularly wound-related infections. Materials and Methods: A retrospective cohort study of all caesarean deliveries during the first quarter of a chosen year was undertaken in our hospital, which is a tertiary referral centre with > 12,000 deliveries per year. Patients’ health records and data from our hospital’s electronic labour and delivery database were reviewed. Data analysis was performed using the Statistical Package for the Social Sciences (SPSS), and odds ratios plus adjusted odd ratios were calculated with 95% confidence intervals (CI). Results: A total of 1829 deliveries were reviewed during our study period. Of these, 180 (9.8%) patients were obese. The rate of caesarean delivery was 48.9% in obese patients versus 28.1% in non-obese patients. Post-operatively, 17% of obese patients experienced wound infection versus 0.2% of non-obese patients. Obese patients were also more likely to experience major postpartum haemorrhage (4.6% vs. 0.2%) and postpartum pyrexia (18.2% vs. 5.0%) in comparison to non-obese patients. Conclusions: Obesity is a significant risk factor in the development of postoperative complications following caesarean section. Wound infection remains a major concern for obese patients undergoing major surgery and results in extensive morbidity during the postnatal period. Postpartum infection can prolong recovery and affect maternal mental health, leading to reduced perinatal bonding with long-term implications on breastfeeding and parenting confidence. This study supports the need for the development of standardized protocols specifically for obese patients undergoing caesarean section. Multidisciplinary team care, in conjunction with anaesthesia, family physicians, and plastic surgery counterparts, early on in the antenatal journey, may be beneficial where wound complications are anticipated and to minimize the burden of postoperative infection in obese mothers.

Keywords: pregnancy, obesity, caesarean, infection

Procedia PDF Downloads 57