Single PC Research Articles

Changes in Serum HOXA9 , PCⅢ, SE-CAD Levels in AML Patients after Chemotherapy with DCAG Regimen and Their Relationship with Prognosis

To investigate the changes in serum homeobox A9 (HOXA9 ), soluble E-cadherin (SE-CAD) and type Ⅲ procollagen (PCⅢ) levels in acute myeloid leukemia (AML) patients after chemotherapy with DCAG regimen and their relationship with prognosis. The clinical data of 80 patients with relapsed/refractory AML diagnosed and treated in our hospital from March 2018 to December 2021 were retrospectively analyzed. According to different treatment regimen, the patients were divided into DCAG group (n=40) and CAG group (n=40). The clinical efficacy and changes of HOXA9 , SE-CAD and PCⅢ levels before and after treatment were compared. In addition, all patients were divided into remission group (n=58) and non-remission group (n=22) according to the clinical efficacy. Univariate and multivariate analyses were performed to analyze the risk factors affecting the prognosis of AML patients. The predictive efficacy of the three single indicators, HOXA9 , SE-CAD, and PC III, and their combination on prognosis was analyzed. Compared with before treatment, the levels of HOXA9 , SE-CAD and PCⅢ in both the DCAG and CAG groups were decreased after treatment, and the improvement of each indicator and the clinical efficacy in the DCAG group were significantly better than those in the CAG group (all P < 0.05). Multivariate analysis showed that increased bone marrow blast count, HOXA9 mRNA, SE-CAD and PCⅢ levels were independent risk factors affecting the efficacy of chemotherapy in AML patients (all P < 0.05). ROC curves showed that the combination of HOXA9 mRNA, SE-CAD and PCIII could effectively predict the prognosis of AML patients, with a sensitivity of 84.80% and a specificity of 88.20%. DCAG regimen can significantly improve the levels of HOXA9 mRNA, SE-CAD and PCⅢ in AML patients, these three indicators are all independent risk factors affecting the prognosis of AML patients, and the combination of the three indicators can effectively predict the prognosis of the patients.

First principles study of electronic structure of x-form phthalocyanine crystals doped with one-dimensional iodine atomic chains

The x-form phthalocyanine (Pc) crystal is composed of a square-lattice arrangement of one-dimensional and double-period molecular chains with molecular planes normal to the stacking direction, and doped iodine (I) atomic chains between these molecular chains are known to induce the insulator-metal transition. Using the van der Waals density functional method, we investigate the electronic structure of a single x-form silicon Pc (x-SiPc) chain and the x-SiPc crystal undoped and doped with I atomic chains in a comparative manner. Although a SiPc molecule has a Si pz derived orbital just above the LUMO, the aligned Si atoms in x-crystals, each of which is at the center of the molecular plane, dimerize in the stacking direction, which prevents formation of a Si metallic band. In a single SiPc chain, two molecules in each primitive unit cell are stacked face-to-face with a staggering angle of 45°. However, when these molecular chains aggregate to create x-crystals, the staggering angle deviates from 45° to about 40° to form H–H bonding orbitals like H2 molecules between neighboring molecular planes in the lateral direction. Doping of the I atomic chains converts half-filling of the doubly degenerate bands to a lower band occupancy, which corresponds to the insulator-metal transition observed experimentally. The equally spaced I atomic chains create a metallic band due to pz-orbital overlapping with an effective-mass ratio of 0.15. Although the SiPc chains operate to create equally spaced I atomic chains, the effect of I atoms trying to trimerize is larger. This trimerization prevents pz orbitals of I atoms from making a metallic band.

Facile synthesis of mechanically robust and injectable tetra-polyethylene glycol/methacrylate chitosan double-network hydrogel cartilage repair

The development of advanced hydrogel scaffolds with good biocompatibility, mechanical strength and bioactive property is highly desirable in cell growth, proliferation, and differentiation for the cartilage tissue regeneration. Herein, we reported a simple, inexpensive, feasible, and environmentally benign strategy to synthesize a biocompatible polyethylene glycol-based methacrylate-modified chitosan (PCSMA) double network (DN) hydrogel via the reversible Schiff base reaction and successive photopolymerization between the tetra-poly (ethylene glycol) aldehyde (Tetra-PEG-CHO) and methacrylate-modified chitosan (CSMA) in mild conditions. The four-terminated CHO groups were hypothesized to not only construct the whole architectural network through the dynamic pH-responsive Schiff base but also contribute to the injectable behavior and good tissue adhesion, which may furnish the surgeon with the availability of injectable and shapeless ability to fill in the gaps. Compared to the single PCS hydrogel with the main similar components of the tetra-PEG-CHO and pure CS moieties, the post-fabrication of PCSMA DN hydrogel possessed slower degradation time, denser network, and stronger mechanical stability, which could facilitate the bone marrow mesenchymal stem cell (BMSCs) activity and promote the chondrogenic differentiation for facilitating cartilage regeneration. Our study highlights the positive effects on chondrogenic performance and supports the PCSMA hydrogel as a promising tissue-engineered scaffold for the cartilage defect repair.

Passively mode-locked fiber lasers dynamic behavior by multimode fiber polarization controller

Passively mode locked fiber lasers (PML-FLs) can produce a variety of phenomena due to the nonlinear effects. With the introduction of the nonlinear polarization rotation (NPR) and a multimode fiber polarization controller (MMF-PC), we observed nonlinear effects in our erbium-doped mode-locked fiber laser, such as the evolution of the soliton bunch to dissipates soliton resonance (DSR) pulses. In the evolution of the soliton bunch to DSR pulses, the soliton square bunch and the multi-longitudinal mode oscillation also appeared in our experiment with the increasing the pump power. To illustrate the importance of MMF-PC, a control experiment is conducted by replacing the MMF-PC with a single mode fiber PC (SMF-PC). The experimental results indicate that the MMF-PC are crucial for the evolution of soliton pairs to DSR pulses and the generation of soliton pairs. The NPR mode-locked structure is used to achieve dual-wavelength filtering, its strength-dependent non-uniform loss can effectively suppress the mode competition in the gain fibers. The MMF-PC in the mode-locked structure adds a polarization burned hole effect inside the resonator. We achieved dual-wavelength mode locking by adjusting the PC to control the birefringence and loss in the resonator.

Conductive Polymer-Based Interactive Shelving System for Real-Time Inventory Management.

Stockouts constitute a major challenge in the retail industry. Stockouts are caused by errors related to manual stockkeeping and by the misplacement of items on shelves. Such errors account for up to 4% of lost sales. Real-time inventory management systems for misplaced items or missing stock detection in retail stores are limited. Accordingly, a conductive polymer-based interactive shelving system for real-time inventory management is developed. The system comprises an 80 × 48 sensor array fabricated by screen-printing a piezoresistive carbon-based conductive polymer layer onto gold interdigitated electrodes deposited on a flexible substrate. Each sensing pixel has dimensions of 5 mm × 5 mm and a sensing area of 4 mm × 4 mm. The sensor mat can detect the shape and weight features of stockkeeping units (SKUs), which can then be analyzed by a TensorFlow model for SKU identification. The developed system is characterized for functional resistance range, uniformity, repeatability, and durability. The accuracy of SKU identification achieved using shape features only and the accuracy of SKU identification achieved using both shape and weight features is 95% and 99.2%, respectively. The key novelty of the work is the development of a deep learning-embedded interactive smart shelving system for retail inventory management by using the shape and weight features of SKU. Also, the developed system helps to detect the SKU if they are stacked one over the other. Furthermore, multiple sensor mats implemented on various shelves in a retail store can be modularized and integrated for monitoring under the control of a single PC. Accordingly, the proposed retail inventory tracking system can facilitate the development of automated "humanless" shops.

Laboratory Access Implementing QR Code Authentication Using OTP

Laboratories in colleges are used to give lectures to students, but what about after working hours? Students can get many benefits from these labs after working hours. For example, students can study and do their homework after working hours. In this project, we have proposed a new technique to control the access of these laboratories. Our idea is to use an encrypted QR code with an TOTP authentication that will be connected to LAN network to guarantee that each student enter can only use a single PC. Each student will have his own encrypted QR code that differs from other students. The TOTP code will be sent to student’s university email. The encryption method used encrypted method used AES encryption to encrypt the data inside the QR code to guarantee the confidentiality, integrity, non-repudiation, and authenticity of the date.

A Damping Control Strategy to Improve the Stability of Multi-Parallel Grid-Connected PCSs

In this study, to ensure stable operation of multi-parallel PCSs, a damping control strategy is adopted to restrain resonance characteristics of a parallel system, and the stability of the system is analyzed. First, the mathematical model of a single PCS is built, the capacitive current feedback-type active damping control strategy is introduced, and the effect of the damping control strategy on a single PCS under proportional-integral (PI) control is analyzed. Then, under the presence of grid impedance, a single PCS model is established and extended to multi-parallel PCSs, where a single PCS is replaced by a Norton’s equivalent circuit. The active damping method is developed, and Bode diagrams are utilized to verify that it can effectively suppress the resonance spikes of a parallel system. Finally, a simulation model of four PCSs in parallel operation is built on the Simulink platform, and the results support the correctness of the theoretical analysis.

Ventricular pacing burden in patients with left bundle branch block after transcatheter aortic valve replacement therapy.

Electrophysiological testing has been proposed in the latest European Society of Cardiology (ESC) guidelines for cardiac pacing to identify left bundle branch block (LBBB) patients with infrahisian conduction delay (IHCD) after transcatheter aortic valve replacement (TAVR). While in general IHCD is defined by a His-ventricular (HV) interval of >55 ms, a cut-off of ≥70 ms to trigger pacemaker (PM) implantation has been proposed in the latest ESC guidelines. The ventricular pacing (VP) burden during follow-up in such patients is largely unknown. As such, we aimed to assess the VP burden during follow-up of patients receiving PM therapy for LBBB after TAVR based on an HV interval > 55 ms and ≥70 ms. All patients with new-onset or pre-existing LBBB after undergoing TAVR at a tertiary referral center underwent EP testing the day after TAVR. In patients with a prolonged HV interval (>55 ms), PM implantation was performed by a trained electrophysiologist in a standardized fashion. All devices were programmed to avoid unnecessary VP by specific algorithms (e.g., AAI-DDD). 701 patients underwent TAVR at the University Hospital of Basel. One hundred seventy-seven patients presented with new-onset or pre-existing LBBB the day following TAVR and underwent EP testing. An HV interval > 55 ms was found in 58 patients (33%) and an HV interval ≥ 70 ms in 21 patients (12%). 51 patients (mean age 84 ± 6.2 years, 45% women) agreed to receive a PM, out of which 20 (39%) patients had an HV Interval over 70 ms. Atrial fibrillation was present in 53% of the patients. A dual chamber PM was implanted in 39 (77%), and a single chamber PC in 12 (23%) patients, respectively. Median follow-up was 21 months. The median VP burden overall was 3%. The median VP burden was not significantly different between patients with an HV ≥ 70 ms (6.5 [0.8-52]) and those with an HV between 55 and 69 ms (2 [0-17], p = .23). 31% of patients demonstrated a VP burden < 1%, 27% 1%-5% and 41% > 5%. The median HV intervals in patients with VP burdens < 1%, 1%-5% and >5% were 66 (IQR 62-70) ms, 66 (IQR 63-74) ms and 68 (IQR 60-72) ms, respectively, p = .52. When only assessing patients with an HV interval 55-69 ms, 36% demonstrated a VP burden of <1%, 29% of 1%-5% and 35% of >5%. In patients with an HV Interval ≥ 70 ms, 25% demonstrated a VP burden < 1%, 25% of 1%-5% and 50% of >5% %, p = .64 (Figure). In patients with LBBB after TAVR and IHCD defined by an HV interval > 55 ms, VP burden is relevant in a non-negligible amount of patients during follow-up. Further studies are warranted to define the optimal cut-off value for the HV interval or to develop risk models incorporating HV measurements and other risk factors to trigger PM implantation in patients with LBBB after TAVR.

Security Analysis of DBTRU Cryptosystem

DBTRU was proposed by Thang and Binh in 2015. As a variant of NTRU, the integer polynomial ring is replaced by two binary truncated polynomial rings . DBTRU has some advantages over NTRU in terms of security and performance. In this paper, we propose a polynomial-time linear algebra attack against the DBTRU cryptosystem, which can break DBTRU for all recommended parameter choices. The paper shows that the plaintext can be achieved in less than 1 s via the linear algebra attack on a single PC.

Blockchain-based IoT system for personalized indoor temperature control

This study aimed to develop a blockchain-based IoT (BIoT) system for adopting automated personalized indoor temperature control to the building management system (BMS) while ensuring data privacy and security. A novel blockchain framework was proposed to register occupants and the personalized thermal sensation vote (TSV) prediction model for training, and control indoor temperatures while ensuring the security of occupant and building data. By implementing the proposed BIoT temperature control system, it could securely transfer about 30,000 personal data for TSV prediction at the same time using a single PC. Moreover, the personalized TSV prediction model could improve accuracy compared to the existing generalized TSV prediction model. As a result, the developed BIoT temperature control system could improve thermal comfort and energy efficiency compared to manual indoor temperature control. Occupants can ultimately be satisfied with the personalized temperature control in every room where required IoT devices are installed without privacy issues.

Design and Optimization of Indoor Space Layout Based on Deep Learning

In order to explore the technical path of using artificial intelligence deep learning algorithm in realizing the interior space layout, this study introduces neural network modules such as 3D spatial convolutional (3DSC) neural networks and fuzzy neural networks (FNN), and a deep learning algorithm of indoor spatial layout design (ISLD) based on the adversarial neural network (ANN) is formed. In the algorithm design, a controllable data-interference adverse variation algorithm based on a random number generator is introduced, to obtain the data variant optimization process of genetic algorithm in neural network deep learning. As shown in the simulation analysis, the algorithm yielded significantly better subjective audience evaluation than other algorithms mentioned in references, and because it can be run offline on a single PC workstation, the demand for network resources and computing power resources is relatively small, so under the premise of the same hardware facility investment, higher production capacity can be obtained to get a higher input-output ratio, and it has a certain industry-university-research transformation and market promotion value.

Real-Time Interactive Simulations of Complex Ionic Cardiac Cell Models in 2D and 3D Heart Structures with GPUs on Personal Computers.

Cardiac modeling in heart structures for the study of arrhythmia mechanisms requires the use of software that runs on supercomputers. Therefore, computational studies are limited to groups with access to computer clusters and personnel with high-performance computing experience. We present how to use and implement WebGL programs via a custom-written library to run and visualize simulations of the most complex ionic models in 2D and 3D, in real time, interactively using the multi-core GPU of a single computer. We use Abubu.js, a library we developed for solving partial differential equations such as those describing crystal growth and fluid flow, along with a newly implemented visualization algorithm, to simulate complex ionic cell models. By combining this library with JavaScript, we allow direct real-time interactions with simulations. We implemented: 1) modification of any model parameters and equations at any time, with direct access to the code while it runs, 2) electrode stimulation anywhere in the 2D/3D tissue with a mouse click, 3) saving the solution of the system at any time to re-initiate the dynamics from saved initial conditions, and 4) rotation/visualization of 3D structures at any angle. As examples of this modeling platform, we implemented a phenomenological cell model and the human ventricular OVVR model (41 variables). In 2D we illustrate the dynamics in an annulus, disk, and square tissue; in 2D and 3D porcine ventricles, we show the initiation of functional/anatomical reentry, spiral wave dynamics in different regimes, initiation of early afterdepolarizations (EADs), and the effects of model parameter variations in real time. We present the first simulations of complex models in anatomical structures with enhanced visualization and extended interactivity that run on a single PC, without software downloads, and as fast as in real-time even for 3D full ventricles.

Real-Time Volumetric Ultrasound Research Platform with 1024 Parallel Transmit and Receive Channels

Volumetric ultrasound imaging is of great importance in many medical fields, especially in cardiology, but also in therapy monitoring applications. For development of new imaging technologies and scanning strategies, it is crucial to be able to use a hardware platform that is as free and flexible as possible and does not restrict the user in his research in any way. For this purpose, multi-channel ultrasound systems are particularly suitable, as they are able to control each individual element of a matrix array without the use of a multiplexer. We set out to develop a fully integrated, compact 1024-channel ultrasound system that provides full access to all transmission parameters and all digitized raw data of each transducer element. For this purpose, we synchronize four research scanners of our latest “DiPhAS” ultrasound research system generation, each with 256 parallel channels, all connected to a single PC on whose GPUs the entire signal processing is performed. All components of the system are housed in a compact, movable 19-inch rack. The system is designed as a general-purpose platform for research in volumetric imaging; however, the first-use case will be therapy monitoring by tracking radiation-sensitive ultrasound contrast agents.

Transformations Among Colloidal Semiconductor Magic-Size Clusters.

A knowledge of colloidal semiconductor magic-size clusters (MSCs) is essential for understanding how fundamental properties evolve during transformations from individual molecules to semiconductor quantum dots (QDs). Compared to QDs, MSCs display much narrower optical absorption bands; the higher cluster stability gives rise to a narrower size distribution. During the production of binary QDs such as II-VI metal (M) chalcogenide (E) ones, binary ME MSCs observed were interpreted as side products and/or the nuclei of QDs. Prior to the current development of our two-step approach followed by our two-pathway model, it had been extremely challenging to synthesize MSCs as a unique product without the nucleation and growth of QDs. With the two-step approach, we have demonstrated that MSCs can be readily engineered as a sole product at room temperature from a prenucleation stage sample, also called an induction period (IP) sample. It is important that we were able to discover that the evolution of the MSCs follows first-order reaction kinetics behavior. Accordingly, we proposed that a new type of compound, termed as "precursor compounds" (PCs) of MSCs, was produced in an IP sample. Such PCs are optically transparent at the absorption peak positions of their MSC counterparts as well as to longer wavelengths. It is thought that quasi isomerization of a single PC results in the development of one MSC.In this Account, we provide an overview of our latest advances regarding the transformations among binary CdE MSCs as well as from binary CdTe to ternary CdTeSe MSCs. Optical absorption spectroscopy has been employed to study these transformations, all of which display well-defined isosbestic points. We have proposed that these MSC to MSC transformations occur via their corresponding PCs, also called immediate PCs. It is reasonable that the as-synthesized PC (in an IP sample) and the immediate PC (in an incubated and/or diluted sample) probably have different configurations. A transformation between two PCs may involve an intermolecular reaction, with either first-order reaction kinetics or a more complicated time profile. A transformation between one immediate PC and its counterpart MSC may contain an intramolecular reaction. The present Account, which addresses the PC-enabled MSC transformations with isosbestic points probed by optical absorption spectroscopy, calls for more experimental and theoretical attention to understand these magic species and their transformation processes more precisely.

Nutrient imbalance diagnosis in walnut orchards by using DRIS and PCA Approaches in the northern part of Erbil governorate-Iraq.

The use of Integrated Diagnosis and Recommendation System (DRIS) on the concept of a plant's nutritional balance has become an efficient method for assessing plant nutritional status; this method places nutrient limitations in order of plant demand, enabling the nutritional balance between the nutrients in the leaf sample. Aim of this study is to establish walnut DRIS norms and diagnosis nutrient imbalance by using DRIS and PCA methods. One hundred four leaf samples were collected during two consecutive years (2016 and 2017) from three walnut orchards in Erbil governorate/ Iraq. The results show that the smallest average NBI values are 125.6 and 27.2 respectively for both studied years which was coincided by high walnut productivity. The most limiting nutrient descending order as Fe&gt;Na&gt;Ca&gt;K&gt;P&gt;N&gt;Mg respectively for first-year samples, and N&gt;Na&gt;P&gt;Fe&gt;Mg&gt;Ca&gt;K respectively for the second year. From the result of principal component analysis (PCA) reveal that the nutrient concentration was explained in the low and high yield subgroups and the DRIS index by 61.95%, 87.75% and 58.67% respectively for first-year and 79.22%, 60% and 65.95% respectively for second-year sampling. Several nutrient interventions in a single PC indicate that no nutrient imbalance in isolation could be diagnosed.

Forecasting coastal overtopping at engineered and naturally defended coastlines

As sea level rises and development of the coastal zone continues, coastal flooding poses an increasing risk to coastal communities. Wave runup can contribute many meters to the vertical reach of the sea, especially on steep gravel beaches, and wave overtopping is a key contributor to coastal flooding along coastlines exposed to energetic wave conditions. However, operational forecasting of wave overtopping has rarely been attempted due to the need for high-resolution inshore water levels and wave conditions, up-to-date coastal profile and sea defence information, and availability of models or formulae that can robustly predict overtopping for a range of coastal profile types. Here, we have developed and tested an efficient forecasting system for providing operational warnings up to three days in advance for the entire 1000 km coastline of southwest England, called SWEEP-OWWL, which is capable of predicting wave runup elevation and overtopping volumes along the energetic and macrotidal coastline, featuring embayed, sandy, gravel, and engineered regions. Existing flood warning systems have used the process-based hydrodynamic model XBeach, but due to the computational cost, have resorted to populating look-up tables using off-line simulations and only a single realisation of the coastal bathymetry. Instead, SWEEP-OWWL runs in ‘real-time’ using a computationally efficient suite of empirical shoaling, breaking, runup, and overtopping equations at 184 coastal profiles, forced with hydrodynamic information from a regional 1-km spectral wave and hydrodynamic model. Importantly, the forecast system can be updated with the latest coastal profile data with no extra computational cost, which is shown to improve the accuracy of predicted overtopping rate by an order of magnitude in some cases. Compared to visual observations of flooding events from live streaming webcams around the southwest, the system correctly predicted the presence or absence of wave overtopping with 97% accuracy and showed skill in differentiating between low and high hazard events. Reliable forecasts of wave overtopping could considerably enhance a coastal community's ability to prepare and mitigate against the risk to life, property, and infrastructure during coastal flooding events, and the developed system shows that this can be achieved using a single desktop PC for entire regions featuring both natural and man-made sea defences.

Development of a Low-Cost Remote Lab Concept for Electronic Engineering Education Based on NI myDAQ and NI ELVIS

Lab work and exercises are an essential part of Electronic Engineering Education as it improves understanding of the theoretical concepts. Remote Labs like VISIR (Virtual Instrument Systems in Reality) can supplement the learning process but are limited to a small set of components. Therefore, experiments with VISIR should be combined with prepared and fixed circuits.&lt;br /&gt;This work presents an approach, where in the first step new exercises are de-veloped with the NI ELVIS platform, and later implemented with the much more cost-effective NI myDAQ platform. In general, the entire system is very inexpen-sive and scaleable, since a single PC can act as a host for a wide number of exer-cise boards, each of which is connected via a myDAQ.

Efficient Processing of Image Processing Applications on CPU/GPU

Heterogeneous systems have gained popularity due to the rapid growth in data and the need for processing this big data to extract useful information. In recent years, many healthcare applications have been developed which use machine learning algorithms to perform tasks such as image classification, object detection, image segmentation, and instance segmentation. The increasing amount of big visual data requires images to be processed efficiently. It is common that we use heterogeneous systems for such type of applications, as processing a huge number of images on a single PC may take months of computation. In heterogeneous systems, data are distributed on different nodes in the system. However, heterogeneous systems do not distribute images based on the computing capabilities of different types of processors in the node; therefore, a slow processor may take much longer to process an image compared to a faster processor. This imbalanced workload distribution observed in heterogeneous systems for image processing applications is the main cause of inefficient execution. In this paper, an efficient workload distribution mechanism for image processing applications is introduced. The proposed approach consists of two phases. In the first phase, image data are divided into an ideal split size and distributed amongst nodes, and in the second phase, image data are further distributed between CPU and GPU according to their computation speeds. Java bindings for OpenCL are used to configure both the CPU and GPU to execute the program. The results have demonstrated that the proposed workload distribution policy efficiently distributes the images in a heterogeneous system for image processing applications and achieves 50% improvements compared to the current state-of-the-art programming frameworks.

Visualization study on the coarse graining DEM for large-scale gas–solid flow systems

Gas–solid flows are ubiquitous in industrial systems. The coupled model of the discrete element method (DEM) and computational fluid dynamics (CFD) is one of the techniques for the simulation of the gas–solid flows. To enhance the applicability of the DEM-CFD method, the coarse graining DEM has been developed to simulate large-scale powder systems. The coarse graining DEM is a scaling law model and hence can simulate large-scale systems using a smaller number of particles than the actual one. Although the coarse graining DEM enables to effectively simulate large-scale powder systems on a single PC, visualized image is lack of reality due to reduced spatial resolution. Here a novel visualization method is developed to produce realistic images. In the proposed technique, the virtual particles are located by considering the motion and location of the coarse grain particles. To show the adequacy of the proposed method, two types of visualization based on the computational results are made: a blow-up of powder due to injected gas flow and a spouted bed. In these systems, the visualized images are shown to be improved by the proposed visualization technique. The effectiveness of the proposed method is proved by the agreement of the images based on the calculation results between the standard DEM-CFD method and coarse graining DEM.

Log Analyzer for Update Manager

Performing System updates is a very tricky and complicated task. You have to update new software on the same old hardware. This may introduce many errors in the system. For example a windows update on a single PC is generally prone to failures. Further updating a server is more challenging job. As a server can support many Operating systems their components, firmware’s and software’s etc, there are many possibilities that a server update may initiate many errors in the system. Thus, this paper proposes a tool that can go through all those thousands of log files generated during an update of a server and finds out where exactly the update went wrong. The paper describes about building a tool to perform log analysis from the scratch. It describes about developing parsers at the backend, building a user interface at the frontend and deploying the tool on to network. The proposed work supports building a Docker for the backend. Docker is a platform as a service product that uses OS-level virtualization to deliver software in packages called containers. The tool takes compressed log file as input. The tool analyses the structure of log file and then parses the contents of the log file according to its structure. Finally the proposed tool generates a report in JSON (JavaScript Object Notation) as well as CSV (Comma-Separated Values) format and that report consists of all the required fields to identify and classify the error that was responsible for failure during system update. This report is sent to concerned software development team to fix the defect that occurred in the update.