Manual Recovery Research Articles

Design and Implementation of an Automated Disaster-Recovery System for a Kubernetes Cluster Using LSTM

With the increasing importance of data in modern business environments, effective data management and protection strategies are gaining increasing research attention. Data protection in a cloud environment is crucial for safeguarding information assets and maintaining sustainable services. This study introduces a system structure that integrates Kubernetes management platforms with backup and restoration tools. This system is designed to immediately detect disasters and automatically recover applications from another Kubernetes cluster. The experimental results show that this system executes the restoration process within 15 s without human intervention, enabling rapid recovery. This, in turn, significantly reduces the potential for delays and errors compared to manual recovery processes, thereby enhancing data management and recovery efficiency in cloud environments. Moreover, our research model predicts the CPU utilization of the cluster using Long Short-Term Memory (LSTM). The necessity of scheduling through this predict is made clearer through comparison with experiments without scheduling, demonstrating its ability to prevent performance degradation. This research highlights the efficiency and necessity of automatic recovery systems in cloud environments, setting a new direction for future research.

ANDeS: An automated nanoliter droplet selection and collection device

The Droplet Microarray (DMA) has emerged as a tool for high-throughput biological and chemical applications by enabling miniaturization and parallelization of experimental processes. Due to its ability to hold hundreds of nanoliter droplets, the DMA enables simple screening and analysis of samples such as cells and biomolecules. However, handling of nanoliter volumes poses a challenge, as manual recovery of nanoliter volumes is not feasible, and traditional laboratory equipment is not suited to work with such low volumes, and small array formats. To tackle this challenge, we developed the Automated Nanoliter Droplet Selection device (ANDeS), a robotic system for automated collection and transfer of nanoliter samples from DMA.ANDeS can automatically collect volumes from 50 to 350 nL from the flat surface of DMA with a movement accuracy of ±30 µm using fused silica capillaries. The system can automatically collect and transfer the droplets from DMA chip into other platforms, such as microtiter plates, conical tubes or another DMA. In addition, to ensure high throughput and multiple droplet collection, the uptake of multiple droplets within a single capillary, separated by air gaps to avoid mixing of the samples within the capillary, was optimized and demonstrated.This study shows the potential of ANDeS in laboratory applications by using it for the collection and transfer of biological samples, contained in nanoliter droplets, for subsequent analysis. The experimental results demonstrate the ability of ANDeS to increase the versatility of the DMA platform by allowing for automated retrieval of nanoliter samples from DMA, which was not possible manually on the level of individual droplets. Therefore, it widens the variety of analytical techniques that can be used for the analysis of content of individual droplets and experiments performed using DMA. Thus, ANDeS opens up opportunities to expand the development of miniaturized assays in such fields as cell screening, omics analysis and combinatorial chemistry.

Design and Experimentation of a Residual-Input Tube-End Cutting System for Plasma Bags Based on Machine Vision

In response to the lack of plasma bag-breaking equipment and time-consuming manual recovery of plasma in China, this study focuses on the distal end cutting of a plasma bag residual-input tube and designs a machine-vision-based plasma bag residual-input tube cutting system. The system comprises a plasma bag rotation device, a bottom disc, an image acquisition device, a cutting device, and a device control system. The image acquisition device captures images of the rotating plasma bag and calculates the Euclidean distance from the end of the plasma bag input-tube distal end to the outer edge of the bottom support plate and the distance from the input-tube distal end to the centerline of the plasma bag. Two distinct value acquisition algorithms are designed for the two types of input tubes. The screw slide moves accordingly. When the plasma bag is above the cutting part, the cutting part cuts the end of the residual-input tube of the plasma bag. The prototype performance tests reveal that the cutting error is within 10% of the end of the plasma bag input tube distal end, the cutting success rate is 100%, and the processing time for each bag is 2.5 s, which meets the time requirements of the plasma bag breaker.

Developing a method for recovering data on storage media

Aim. The development of digital technology brings about the need to digitize data with their subsequent storage on digital media. Regardless of how information is stored, it is of value and its loss may cause harm. There are a number of preventive measures (hardware and logical redundancy of various types) to prevent such loss. Should the preventive measures – due to certain reasons and circumstances – fail to protect the data and access to the latter was lost, it must be recovered in a complete and timely manner. In this context, a need arises for a data recovery algorithm that would take into account the hardware features of today’s storage media, their logical structure, as well as the specificity of the stored data. Methods. There are two approaches to information recovery, i.e., all-purpose and personal. The all-purpose approach involves using a minimal number of programs and tools that work with all items. The personal approach implies a large number of programs and tools that address specific issues associated with the loss of access to information. That enables a faster, higher-quality recovery as compared to the all-purpose approach. Additionally, personal programs are normally cheaper than all-purpose software. All-purpose information recovery tools do not provide quality results when applied to large numbers of failure scenarios. A single utility may not be enough for resolving all issues caused by an incident. A readily available template for obtaining an acceptable result does not exist either. Aside from personal software, there are other alternatives to the all-purpose approach, i.e., the manual data recovery programs and hardware and software systems. In cases of minor logical faults (master boot record corruption) manual data recovery software is used. If a drive is affected by critical hardware issues, hardware and software systems are used. Results. A method of recovering data on storage media of various types was created. It includes an all-purpose and a personal approaches to information recovery, use of software for manual data recovery, as well as hardware and software systems. The method allows recovering data of popular extensions from common file systems and storage media. Compatibility with RAID arrays of all levels is provided. Programs were selected out of eight sets using the analytic hierarchy process with the priority given to the performance criterion. The method was submitted to a number of tests. Testing involved emulation of incidents associated with the loss of access to data. The cost of eliminating various incidents using the developed methodology is estimated. Conclusions. Based on the obtained test results, conclusions are set forth regarding the efficiency of the personal approach to information recovery.

Multi-stage Vibrating Screen Mulching Film Removing Device Based on Plastic Thermoplastic Principle

In view of the increasingly serious agricultural white pollution, this project has designed a multi-stage vibrating screen film removal device based on the principle of plastic thermoplasticity. The whole is installed behind the seeder body and works in cooperation with the seeder. The device is composed of a film gripping module, a deep turning module, a crushing module and a graded vibrating screen module, and realizes the process of bringing out the film in the soil, crushing it, fining it and finally collecting it. At the same time, according to the state of the recovered film, a graded vibrating screen module is designed. The first-stage vibrating screen can transport the soil and film to the second-stage vibrating screen device, and the second-stage vibrating screen device separates the film by using the thermoplasticity of the mulching film by heating, so that the film can be better separated and recovered. The novel high-efficiency mulching film removing device can avoid the problem of low efficiency of traditional manual recovery. Compared with the existing device, it improves the rate of removing mulch film, effectively reduces the influence of residual mulch film on the environment, lightens the white pollution, and has good energy saving and emission reduction benefits.

The artificial digestion method underestimates the viability of Anisakis simplex (s.l.) L3 present in processed fish products

This work studied the performance of the artificial digestion method in terms of recovery and viability of Anisakis simplex third-stage larvae (L3) when previous treatments given to the infected fish muscle may accidentally render viable larvae. For that: a) hake mince was spiked with 10 L3/75g mince, frozen at −10, −15, −20, and −30°C and immediately thawed, or stored for 12 or 24h, and subjected to pepsin digestion; b) the mince was spiked under the same conditions, frozen at the above temperatures and thawed immediately. After manual recovery, L3 were assessed for viability, used to spike again the minced fish and subjected to pepsin digestion; c) the mince was spiked with 10 L3 which were: i) living (i.e. chilled), ii) freeze-surviving (live L3 had been previously recovered after freezing at −10°C), or iii) dead (frozen at −30°C or−80°C), and then subjected to pepsin digestion. Results showed that the artificial digestion method kills a significant number of larvae that may have survived freezing and thus may underestimate the number of viable larvae in a given batch. The method may also underestimate the infection level of fish batches containing dead larvae. It is suggested to take these limitations into account when designing digestion protocols for specific applications, especially when there is a risk of insufficiently treated or cooked fish batches or ready-to-eat foods.

Research on the Application of Automatic Monitoring Software for Seismic Observation Instruments

Combining with the actual monitoring work of seismic geophysical observation stations, a seismic monitoring instrument automatic monitoring software was developed. The software is suitable for real-time or regular automatic network monitoring of IP instruments and equipment under different network environments. Automatic monitoring of the clock, status and observation data of geophysical observation instruments, which can automatically identify invalid data and abnormal amplitude changes in the observation data of the day, interference, earthquake and amplitude limitation, etc. Without other hardware and software, the alarm information can be sent to the duty personnel and management personnel by SMS, which can realize automatic backup and manual recovery of the original observation data of the instrument, and One-click restart and clock correction and other control operations, you can view the integrity and validity of the observed data curve and analysis data of the day without cross-platform operation, thereby achieving unified and efficient management of the instrument.

An explorative object-oriented Bayesian network model for oil spill response in the Arctic Ocean

This paper proposes an Object-Oriented Bayesian Network model to study oil spill mitigative measures using cost-effectiveness as a decision-making factor. The cost-effectiveness is defined as the ratio of dollar spent to the efficiency of oil removal in the spill area. The proposed model considers the complexity, lack of data, and uncertainties in an oil spill and response modelling scenario for Arctic shipping accident occurrence. The crude oil release, slick formation, weathering and transport, ecological impact, and response scenarios are modelled using Bayesian Network. Application of the model is demonstrated using a hypothetical scenario of an oil spill involving a ship in the Arctic region. The results show that a combination of in-situ burning, mechanical and manual recovery, and use of dispersants would cost the highest, while the use of in-situ burning, and dispersants gives the cheapest option. The study provides a deeper understanding of oil spill dynamics and effectiveness of the response techniques. The proposed model could serve as a useful tool for oil spill response decision-making.

Manual Recovery of a Sea Ice Based Ocean Profiler

Ice-tethered ocean profiling systems are an essential tool for the year-round observation of physical and biogeochemical properties of the Arctic Ocean. Despite being considered expendable equipment due to the challenging logistics, their recovery is attractive mainly due to two factors: If the sensors can be retrieved, this allows for their post calibration, which helps to assess sensor drift and biofouling. In addition, the recovery of such expensive equipment can ease off financial pressure on autonomous ocean observation programs by enabling the reuse of central elements after refurbishment. Here we present a method how such profiling systems can be recovered from sea ice by 3 people in about 4 hours, without the on-site availability of a fully-equipped vessel. The presented technique combines rope techniques from mountain rescue applications with lightweight equipment and procedures similar to those used for the deployment of such instruments. We provide a detailed description of the whole process, provide suggestions for potential improvements as well as suggestions towards improved instrument design favoring recoverability of future deployments. We conclude that good preparation and practice of the relevant rope procedures is critical to mission success and that a well selected range of necessary equipment makes the process much more efficient.

Greenhouse gas emission offsetting by refrigerant recovery from WEEE: A case study on a WEEE recycling plant in Korea

The demand for new electrical and electronic equipment (EEE) has resulted in short replacement cycles for this equipment. This has led to the generation of a large amount of waste electrical and electronic equipment (WEEE). The proper disposal of WEEE is essential in order to manage greenhouse gas (GHG) emissions, as refrigerant injected EEE is a potential source of GHG emissions. In this study, carbon dioxide (CO2) emissions from recycling activities that resulted in GHG emissions via refrigerant recovery were quantitatively evaluated. The evaluation was conducted based on the operational data from a WEEE recycling plant in 2016. To estimate CO2 emission and offsetting effects, mass-balance and carbon-footprint analyses were conducted. The mass-balance data showed that 22,804 t of WEEE were recycled in a plant. The carbon-footprint analysis estimated that CO2 emissions from all recycling activities, including all machinery and vehicles as well as fossil fuel and electricity use, reached approximately 4.097 × 103 tonne of CO2 eq. Meanwhile, the CO2 emissions prevented by the manual recovery of refrigerants (5186 kg) from WEEE accounted for approximately 2.877 × 104 tonne of CO2 eq. These results, based on data from a recycling plant and showing an offset of CO2 emissions by a factor of 7.02, demonstrate that refrigerant recovery could potentially reduce emissions by 2.467 × 104 tonne of CO2 eq. per year. This study will demonstrate the optimal methodologies for estimating CO2 emissions and offsetting, and inform environmental policy by providing an alternative approach to the problem of global warming.

Recovering energy biomass from sustainable forestry using local labor resources

Logging residues from sustainable forest operations can be recovered as biomass feedstock for renewable energy generation. Under the conditions of developing economies, residue recovery is best performed with manual techniques, because labour cost is still low, whereas capital availability is limited. Furthermore, manual recovery minimizes fossil inputs and creates employment opportunity for self-employed forest villagers in disadvantaged rural areas, and it may help contrasting landscape neglect and rampant urbanization. This study offers the example of residue recovery from the regeneration cut of mature Turkish pine (Pinus brutia Ten.). Even after all stem and branch portions are recovered to a minimum small-end diameter of 4 cm for the production of conventional firewood logs, residues amount to 15–30 fresh t ha−1 and require windrowing before replanting. Approximately 50% of the residue can be recovered as energy biomass, after separating the fibre rich portion from twigs and leaves. This operation allows additional recovery, while minimizing nutrient removal. Productivity was estimated between 0.3 and 0.7 fresh t h−1, for a three-men crew. Manual extraction of processed residues to the roadside proceeded at a pace between 0.8 and 1.7 fresh t h−1 for the same crew. Best results were obtained when processing was performed after removing all conventional product, and before windrowing the residues. The most effective extraction method was throwing the biomass sticks downhill to the roadside. Processing and extraction cost amounted to 27 € fresh t−1, or 8.3 € MWh−1. After accounting for delay time, for chipping, transportation and all other indirect cost, total delivered cost amounted to 14.3 € MWh−1. That was over the 10 € MWh−1 target, indicating the need for increased efficiency, possibly obtained through better mechanization. The results of this study might be generalized and extended to many other developing economies, where the rational recovery of logging residues may offer significant economic, environmental and social benefits.

Vitality of Neural Networks under Reoccurring Catastrophic Failures.

Catastrophic failures are complete and sudden collapses in the activity of large networks such as economics, electrical power grids and computer networks, which typically require a manual recovery process. Here we experimentally show that excitatory neural networks are governed by a non-Poissonian reoccurrence of catastrophic failures, where their repetition time follows a multimodal distribution characterized by a few tenths of a second and tens of seconds timescales. The mechanism underlying the termination and reappearance of network activity is quantitatively shown here to be associated with nodal time-dependent features, neuronal plasticity, where hyperactive nodes damage the response capability of their neighbors. It presents a complementary mechanism for the emergence of Poissonian catastrophic failures from damage conductivity. The effect that hyperactive nodes degenerate their neighbors represents a type of local competition which is a common feature in the dynamics of real-world complex networks, whereas their spontaneous recoveries represent a vitality which enhances reliable functionality.

Developing a unit selection voice given audio without corresponding text

Today, a large amount of audio data is available on the web in the form of audiobooks, podcasts, video lectures, video blogs, news bulletins, etc. In addition, we can effortlessly record and store audio data such as a read, lecture, or impromptu speech on handheld devices. These data are rich in prosody and provide a plethora of voices to choose from, and their availability can significantly reduce the overhead of data preparation and help rapid building of synthetic voices. But, a few problems are associated with readily using this data such as (1) these audio files are generally long, and audio-transcription alignment is memory intensive; (2) precise corresponding transcriptions are unavailable, (3) many times, no transcriptions are available at all; (4) the audio may contain dis-fluencies and non-speech noises, since they are not specifically recorded for building synthetic voices; and (5) if we obtain automatic transcripts, they will not be error free. Earlier works on long audio alignment addressing the first and second issue generally preferred reasonable transcripts and mainly focused on (1) less manual intervention, (2) mispronunciation detection, and (3) segmentation error recovery. In this work, we use a large vocabulary public domain automatic speech recognition (ASR) system to obtain transcripts, followed by confidence measure-based data pruning which together address the five issues with the found data and also ensure the above three points. For proof of concept, we build voices in the English language using an audiobook (read speech) in a female voice from LibriVox and a lecture (spontaneous speech) in a male voice from Coursera, using both reference and hypotheses transcriptions, and evaluate them in terms of intelligibility and naturalness with the help of a perceptual listening test on the Blizzard 2013 corpus.

Evolved intelligent clustered bee colony for voltage stability prediction on power transmission system

Very often, voltage instability causes millions of money to cater with the negative effects it gave to the people; therefore, it is very important that prior to this worst situation, some manual or automatic recovery system had to be turn on to minimize or totally avoid the entire situation. But these recovery systems will not be turn on if there is no good indication or alarm that controls or informs. In this paper, evolved intelligent clustered artificial bee colony (EICBC) is introduced to predict the voltage stability condition of the IEEE 30-bus test system. Fast Voltage Stability Index is utilized as an indicator to measure the distance of the power system network to the voltage collapse point when the reactive load is varied slowly as reactive load gives the most impact on the stability of the system. EICBC is able to converge faster to its best solution while maintaining the stability of the prediction system by avoiding local minima convergence. The results also show that the proposed algorithm is superior in the prediction accuracy and can be used to categorize the conditions of the network for the ease of identification.

Recovery of spray paint traces from clothing by beating.

Manual recovery of spray paints from textiles using a microscope, the routine method in many laboratories, is often laborious. Beating the clothing with a plastic rod, the routine method used for recovery of glass traces within the authors' laboratory, is proposed as an alternative. The efficiency of the method was evaluated by spray tests with fluorescent paint. In these tests, paint particles in the acquired debris samples, as well as those remaining on the textiles, were investigated. The results show that beating is an efficient way to recover and concentrate paint particles. A good efficiency for jeans fabric and rough knitwear is reported. The results appeared to be less satisfactory for smooth woven fabric. Application of the method in casework was effective for graffiti paints as well as for flaked car paint.

Profit Analysis in Some Redundant Systems With Repair Maintenance

This paper deals with modularly redundant system with many active units and a warm standby unit. The concepts of 'coverage' and 'manual recovery' have been incorporated. Probabilities that the system can recover automatically/manually at the time of failure of an active unit, are fixed. Failure of an active unit , are fixed. Failure time distributions of an active and standby units are exponential with different rates. However, distributions of time to repair a failed unit, recovery device, time to manual recovery are taken as general. It is assumed that the system earns a fixed amount for the duration it is operative and repair cost is incurred when a unit/RD is under repair. Expected profit of the system has been obtained by superimposing Howard's reward structures on the semi Markov process generated by the system model. System performance (expected profit) has been studied for its behaviour. Several earlier well known models are included as special cases.

Development and Field Test of Voltage VAR Optimization in the Korean Smart Distribution Management System

This paper is a summary of the development and demonstration of an optimization program, voltage VAR optimization (VVO), in the Korean Smart Distribution Management System (KSDMS). KSDMS was developed to address the lack of receptivity of distributed generators (DGs), standardization and compatibility, and manual failure recovery in the existing Korean automated distribution system. Focusing on the lack of receptivity of DGs, we developed a real-time system analysis and control program. The KSDMS VVO enhances manual system operation of the existing distribution system and provides a solution with all control equipment operated at a system level. The developed VVO is an optimal power flow (OPF) method that resolves violations, minimizes switching costs, and minimizes loss, and its function can vary depending on the operator’s command. The sequential mixed integer linear programming (SMILP) method was adopted to find the solution of the OPF. We tested the precision of the proposed VVO on selected simulated systems and its applicability to actual systems at two substations on the Jeju Island. Running the KSDMS VVO on a regular basis improved system stability, and it also raised no issues regarding its applicability to actual systems.

Development of a biology inspired manufacturing system for machining transmission cases

Disruptions in automated manufacturing systems for machining automotive parts caused by system changes and disturbances reduce the productivity, and increase the downtime as well as the cost of products. To cope with these challenges, the paper presents a biology inspired manufacturing system (Bio-MS). The model of Bio-MS is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee’s foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To realize the Bio-MS, the cognitive agent and swarm intelligence were proposed. The disturbances happening when machining the transmission cases at an automotive company in Korea were analyzed to classify them and to find out the corresponding management methods. Currently, the system utilization was too low due to the manual recovery, only 70–76 percent of total production time is used for manufacturing and the rest of the time is wasted in different disturbances. The Bio-MS with autonomous behaviors adapts efficiently to the changes of the manufacturing environment. It enables to increase the system utilization more than 80 percent.

Embedded UPS Remote Control Management System Based on ARM

Design an Embedded UPS Remote Control and Management System with S3C2440. Remote control discharge, field manual discharge, regular maintenance for discharge operation, remote and manual power recovery operation can be realized through INTRANET LAN and field terminal. Further more, overdischarging protection, power abnormal protection, fault alarm, field data collection and upload are also achieved, which makes the system widely applied in the field of bank and hospital.

ANÁLISE DE CARVÃO VEGETAL MACROSCÓPICO EM PORÇÕES DO SÍTIO ARQUEOLÓGICO RS-T-101, MARQUES DE SOUZA/RIO GRANDE DO SUL, BRASIL

Anthracology is a multidisciplinary discipline that allows the analysis of charcoal preserved in soils and archaeological sites, for the purpose of studies on climate, vegetation and man-made activities. In order to characterize the fuel used by pre-colonial populations, the present study evaluated the occurrence of charcoal in a Quaternary Age archaeological site in the municipality of Marques de Souza, Rio Grande do Sul state. Macroscopic charcoal fragments were collected from the archaeological site. Using the scheduling technique, process that consists in the layering of the excavation by blasting followed by manual recovery of fragments that resembled charcoal. Samples were analyzed by naked eye and under stereomicroscope. Those wich could be characterized as having charcoal, were separated mechanically and the fragments removed with the aid of spatula, tong and histological needle. The material was examined under SEM (Scanning Electron Microscope) for the establishment of taxonomic affinities. Based on the data was possible to rescue charcoal in a good state of preservation, and defined a combustion temperature between 230o-340o C, observing homogenized cell walls. It was also possible to observe cellular structures in good condition, identifying the fragments as belonging to angiosperms. One of the samples showed the presence of fusioned fungal hyphae.