esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Bread Characterization
#### 3.2.7 Sensory Analysis
[50] observed that NaCl replacement with PanSalt(r) [NaCl 57%, other salts and minor ingredients] at 1.5% or 3% failed to maintain the saltiness level of bread and turned it sweeter compared to the NaCl counterparts. However, the overall flavour intensity of bread with 1.5% PanSalt(r) did not differ from 1.5% NaCl bread and no undesirable flavours were perceived. Moreover, the overall liking did not differ between the 1.5% NaCl and 1.5% PanSalt(r) beads but the higher value of PanSalt(r) produced a perceptible increase in bitter taste and aftertaste in the crust. These finding emphasize that replacing NaCl with KCl-based replacers could impact in the overall flavour perception rather than the perception of salts taste. Moreover, the bread salt-reduction claims influence sensory expectations and perception. Thus, it is critical to determine the quantity of NaCl replacement without affecting the product's characteristics and sensory attributes and to familiarize the consumers with the changed taste, regardless of the sodium reduction strategy used to replace salt.
# Research Progress on the Mechanisms and Control Methods of Rockbursts under Water-Rock Interactions
## 3 Research Progress on Water's Impact in Strain-Induced Rockburst Experiments
### Study on the Mechanical Properties of Sandstone under Wet-Dry Cyclic Conditions
This method applies either static or dynamic loads to mimic the stress conditions in natural environments. Both experimental techniques are standard in material mechanics testing and provide precise measurements of material properties. Overall, these three studies examined the mechanical properties of sandstone under wet and dry cyclic conditions. They used experimental techniques to assess physical properties such as dynamic elastic modulus, tensile strength, and compressive strength, revealing that wet and dry cycles have a significant impact on these properties. Additionally, [PERSON] et al. [56] specifically investigated how these cycles affect the fracture behavior and damage mechanisms of sandstone.
## 2 Average Power Scaling of Modelocked Thin-Disk Lasers: Challenges and Milestones
### State-of-the Art Modelocked Thin-Disk Laser with 275 W of Average Power
#### 2.2.2 Discussion  
Inside the oscillator, the circulating pulses had an energy of 146 \(\upmu\)J, and a peak power of 220 MW. In contrast to previous high-power modelocked TDLs, the nonlinearity of the ambient environment was not the main contribution to the total SPM phase shift (Table 1). Assuming soliton pulses, the dispersion introduced in our cavity compensates for a nonlinear phase shift of approximately 75 mrad at the maximum power and for the obtained pulse duration. The atmosphere in the cavity only contributes \(\approx\)8 mrad to this total phase shift, assuming a linear behavior of the nonlinear refractive index of air with the pressure in the vacuum chamber [35,39]. The Brewster plate accounts for \(\approx\)17 mrad and the thin disk for \(\approx\)3 mrad. The remaining phase shift (\(\approx\)47 mrad) seems to originate from nonlinearities due the high intensities on the different cavity mirrors. In our current layout, some of the dielectric mirrors used in the cavity withstand intensities \(>\)50 GW/cm\({}^{2}\). At these high peak intensities, even a small penetration depth can lead to a significant phase shift. However, in order to precisely evaluate  
Figure 5: **(a)** Autocorrelation trace of the pulses at the maximum average output power of 275 W; **(b)** Optical spectrum of the pulses; **(c)** Radio frequency spectrum of the pulses, with a resolution bandwidth of 30 kHz; **(d)** Output power and optical-to-optical efficiency in modelocked operation as a function of pump power. The points before modelocking were not measured in order to avoid damage of intracavity components during the Q-switched modelocking (QML) regime that occurs before modelocked operation.  
the contribution of each mirror to the total phase shift, the exact structure and material composition of these commercial mirrors needs to be precisely known. This point is currently being investigated.  
In spite of these very high intracavity intensities, no damage was observed on the SESAM. The main limitation to higher average powers in our current configuration was thermal effects and even damage that occurred in the dispersive mirrors. Improved dispersive mirror designs with better thermal properties will allow for higher average power in the future.
## 2 Materials and Methods
### GC-QTOF-MS Analysis
#### 2.3.2 Chromatographic Conditions  
The GC-QTOF-MS instrument comprised of 7890A gas chromatograph and 7200 QTOF mass spectrometer, equipped with an electron ionization (EI) source, obtained from Agilent (Wilmington, DE, USA). Automated recalibration of the mass axis was carried out every 6 injections. Two same columns used for compound separation were DB-5 MS capillary columns (15 m \(\times\) 0.25 mm \(\times\) 0.25 \(\upmu\)m), which were also acquired from Agilent. Helium was used as carrier gas at a constant flow of 1.2 mL min\({}^{-1}\) and the column temperature was programed as follows: 30 \({}^{\circ}\)C (4 min), rated at 3 \({}^{\circ}\)C min\({}^{-1}\) to 110 \({}^{\circ}\)C (2 min), and finally at 20 \({}^{\circ}\)C min\({}^{-1}\) to 260 \({}^{\circ}\)C with a hold time of 1 min. Injections were made in the splitless mode. The transfer line and the EI source were set at 280 and 230 \({}^{\circ}\)C, respectively. The solvent delay was fixed at 3 min. The mass range was 40-350 \(m/z\). Perfluorotributylamine was used for the daily mass calibration and as lock mass, and the \(m/z\) ion monitored was 218.9856. The TOF mass analyzer was operated in the 2 GHz mode. TOF-MS resolution was approximately 7000 (FWHM). Library search was performed using the commercial NIST library.
## 4 Data Acquisition and Parallel Design and Implementation of MIR Algorithm
### Identifying the Parallelism of MIR Algorithm  
To identify the parallelism in the MIR algorithm, the sequential implementation is analyzed to find the time-intensive part, as well as the dependency among processes. The most compute-intensive part is the number of iterations required to construct a matrix of pixel values for an image, due to multiple iterations and massive input data. In the process, each iteration contains many parallel processes, creating an opportunity for parallel design and implementation. The number of iterations required for the reconstruction of one image is explained as follows:  
Suppose \(P_{1}\), \(P_{2}\)... \(P_{n}\) are the patients, and \(D_{1}\), \(D_{2}\)...\(D_{n}\) denotes the number of times each patient is diagnosed and the data is stored. So, we have  
\[C_{r}=\sum_{p=1}^{n}\sum_{d=1}^{n}P_{i}D_{i}A_{n}N_{ip}, \tag{3}\]  
where \(N_{ip}\) denote input points stored, and \(P_{i}\) and \(D_{i}\) denote patients and diagnostics, respectively.  
For instance, if the number of input points (data) for each antenna is 200 (minimum required data points for image reconstructions reported in Reference [53; 54]) and 06 antennas: 200 \(\times\) 6 \(\times\) 100 \(\times\) 100 = 12,000,000 iterations is required to reconstruct an image of 100 \(\times\) 100 pixels.  
The most time-consuming part of the algorithm is delay calculations and pixel value calculations. To make each of these calculations more efficient, there is a need to implement a parallel algorithm that executes these data on multiple nodes in the cluster using big-data frameworks, such as Spark or Hadoop Ecosystem. The signal samples and location of antennas are uploaded to the Eddie distributed file system, and stored in distributed manner, which is input to the MIR algorithm.  
According to the MIR algorithm, explained in Section 3, in order to calculate pixel points from input data, delay values need to be calculated first. Since it needs to be calculated once only, its parallel implementation therefore does not have any substantial effect on the efficiency of the algorithm. The most intensive part is the pixels value calculation, which needs to be parallelized. During this process, pixel values in different subsets are independent of each other; hence, the calculation of each pixel value in different subsets on different machines in the cluster is a good fit for parallelism.
# A Fully Automated Pipeline for a Robust Conjunctival Hyperenia Estimation
## 2 Materials and Methods
### Image Processing Pipeline
#### 2.4.2 Step 2--Vessels Network Segmentation  
The conjunctiva segmentation allows for reducing the region of interest of our analysis on the most informative area for the redness evaluation. The first step of processing involves a standardization of the images and the correction of the light dependence due to uneven illumination of the conjunctiva. In the same image, different parts of the conjunctiva could have different brightness based on the angle of the incidental light on the conjunctiva and the aperture of the slit lamp diaphragm. This different brightness produces images with a shadow component or with a flash glare. The vessels network in the conjunctiva can thus appear as a brighter or a darker red component, and this can drastically affect the redness evaluation. The images, in fact, tend to appear with a heterogeneous red component when the acquisition is performed in low-light situations. At the same time, the light standardization allows for removing the possible shadows or hyper-intense areas due to the effect of the flash over the patient's eyes. This standardization is performed independently on each channel of the image (R, G, and B), and it involves a median blurring of the channels followed by a normalization of the difference between the blurred and the original channel. The resulting standardized image is converted into grayscale before the application of the next steps.  
Starting from the standardized masks, the pipeline performs the vessel segmentation. The vessels' network segmentation is a standard task in ophthalmology image processing, and many studies have already published promising results on this topic [3; 9; 10; 19; 27; 28]. In our work, we decided to use a customized version of the method proposed in [19], using a watershed adaptive filter to highlight the network vessel component and to segment it from the background. After removing the smaller connected components (up to a predetermined size) to remove noise artifacts, the resulting segmentation is refined using a GuoHall skeletonizer [29]. In this way, only the backbone (only 1 pixel for each branch) of the vessels network is selected. In the next steps, we use the backbone network as a mask for the extraction of the redness features, focusing our analysis on the smallest but most informative region of the image.
## 2 Background and Literature Review
### Popular Architecture using HMT Framework  
The architecture of the system must be approved at an early stage of the project in order to avoid pricey variations later. In addition, it is important to build the base for a practical HMT architecture by defining the basic essential blocks. To accomplish this, we surveyed 27 frameworks and shortlisted six, based on the presence of essential blocks. We then adapted them to state-of-the-art technology and decided nine essential blocks as a basic HMT framework, namely human-machine interaction (HMI), information, system state control, arbitration, goal recognition and mission planning, dynamic task allocation, rules and roles, validation and verification, and training [13; 33]. The different types of architectures that we studied are Pilot's Associate Architecture, 3 Tier Intelligent Framework, Crew Assistant, Human Machine Co-operation framework, Intelligent Control  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Functional Block/ Framework** & **HMI** & **Information** & **System State Control** & **Mission Planning \& Dynamic Task Allocation** \\ \hline Pilot’s Associate & Primitive, no & Primitive, no & No & Not available & Primitive \\  & HMT support & HMT support & & & \\ \hline
3 Tier Intelligent & Primitive, no & Real-time & & & \\ Framework & HMT support & monitoring & Yes & Human-based & Machine-based \\ \hline Crew Assistant & Moderate, no & Real-time & & & \\  & HMT support & monitoring & No & Human-based & Machine-based \\ \hline Human-machine & Theoretically & Real-time & Yes & & \\ Co-op Framework & supports HMT & monitoring & (in theory) & Machine-based & Machine-based \\ \hline Intelligent & Primitive, & Real-time & & & \\ Control Framework & working model & monitoring & Yes & Human-based & Machine-based \\ \hline Coactive Design & Primitive, & Real-time & & & \\  & working model & monitoring & Yes & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of all six methods in inclusion of required components.  
Framework, and Coactive Design Framework. A tabulated analysis of the six major frameworks studied is presented in Table 1, with functional blocks representing how they achieved functions and automation methods.
# Routing Path Assignment for Joint Load Balancing and Fast Failure Recovery in IP Network
## 3 Optimization Models  
This section presents the proposed ILP models for working and backup path planning in a Fibbing-controlled IP network. The objective function of these optimization models is to minimize the load on the most congested link when the network is in its normal state. We include network survivability constraints so every upstream node can have at least one neighbor node with either an R1, R2, or R3 neighbor. The output of the ILP  
Figure 6: OSPF weight and fake nodes assignment to realize the desired routing paths with given bifurcating ratios for traffic towards destination D in the normal state.  
programs is used to configure fake nodes in the network. To make comparisons, we first present the LBO formulation that only considers load balancing. Because the survivability constraints are not included in the formulation, the working paths obtained from the problem minimize the load on the most congested link. We use the results from LBO as a lower bound to justify the results when survivability constraints are included.
# The Risk Assessment of the Security of Electronic Health Records Using Risk Matrix
## 8 Real-Life Use Case  
Healthcare professionals can protect the organization they work for by receiving training on security best practices and following them. Most security breaches are the result of employees misusing their access to healthcare records. Using personal devices is one way that healthcare professionals violate the privacy of their patients, as their devices are not secure. A ban on personal electronic devices can eliminate the issue of insecure personal devices being used to access EHRs.  
Most security breaches in organizations start with phishing attacks, where a cyber attacker uses an employee's stolen credentials to access the organization's data. A knowledge workforce is critical to protecting an organization, as employees will protect their credentials and observe security best practices, such as not opening suspicious emails that contain the malware used in phishing attacks. Training employees on the best security methods is the best strategy an organization can use to protect itself.  
Besides the human factor, cyber attackers have developed sophisticated technology and skills to compromise an organization's security. To counteract such advances, organizations have to use the latest security technology to protect their sensitive data. Next-generation firewalls have become essential for computer systems. These firewalls have the capacity to filter traffic according to set policies and have the capabilities of intrusion detection and prevention systems (IDSs/IPSs), which detect traffic anomalies and prevent them. Also, modern firewalls have machine learning capabilities to understand traffic and detect anomalies in outbound and inbound traffic. Next-generation firewalls are essential for healthcare organizations, as they protect their data from being accessed through suspicious ports and alert network administrators of suspicious activities, helping them understand the types of attacks and thus improve their security.  
Access control is mandatory for any organization to prevent any employee, group, or team from having a large amount of information that can compromise the organization. For EHRs, access control ensures that each person has limited access to information, making it hard for any one individual to access complete patient profiles and reducing the chances of cyber attackers or insiders using one account to access patients' data. Access control is mainly ensured through role-based access, where each employee has access according to their role. The billing department only has information about patients' expenses, while physicians have the patient's medical history. The front desk only has patients' appointments. Such access makes it hard to build a profile of an individual and thus adds an extra layer of security to EHRs. Here is the Risk matrix of real-life use cases (Figure 3).
# Minimum Viable Products for Internet of Things Applications: Common Pitfalls and Practices
## 4 Results
### RQ1: How Do Internet of Things Start-Ups Build Their MVPs in the Early Stage? #### 4.1.1 Key MVPs from Internet of Things Start-Ups  
The interviewee was asked about the MVPs that are critical for their start-ups in the early stage. This does not mean each start-up produces only these MVPs. Many MVPs can be created but start-ups only focused on describing one MVP that is most important for them at their early stages. The role of the MVPs can be to acquire funding, to attract customers or to recruit team members and so forth. Table 3 presents the descriptions of these major MVPs in our eight hardware-start-ups. For each MVP, we also specify the software/hardware components were developed, the time used to complete the MVPs and grouping them into three groups. MVP creation duration varies from three months to 28 months. The process started since ideas were agreed among the team until the MVP is ready for its purpose. Several activities are included in the prototyping process, from research and development (R&D) activities, market and customer research, preparation of tools and necessary components, physical design, implementation and testing. The varied durations depend on the MVPs themselves and contextual factors:  
* In Case H, the MVP was done in a short time (3 months). The major MVP was quite simple with no physical unit design. The significant amount of time was spent on conceptual design and sketching features. The team ordered available electronics units and integrated into the software part. The team focused on a front-end design of the software product. The integration was based on a 3 rd party service provider. * In case C, the MVP was complete in a very long time (28 months). The prototyping process is lengthy due to the complexity of the hardware design and the part-time nature of the participation of the founders. The core part of the MVP is the design of the camera. Besides many architectural elements were bought, other elements were designed in-house, which takes time. The MVP heavily depended on open-source components for both hardware and software parts. Based on the similarities in objectives and methodologies of the development of MVPs, we classify the Internet of Things start-ups' MVPs into three types: piecemeal MVPs (MVP type 1), functional MVPs (MVP type 2) and non-functional MVPs (MVP type 3), as shown in Figure 4. An MVP can be used as the basis to develop the next MVP or incremental prototyping.
###### Abstract  
Energy demand and consumption have, in recent times, witnessed a rapid proliferation influenced by technological developments, increased population and economic growth. This has fuelled research trends in the domain of energy management employing tri-generation systems such as combined cooling, heating and power (CCHP) systems. Furthermore, the incorporation of renewable energy, especially solar energy, to complement the thermal input of fossil fuels has facilitated the effectiveness and sustainability of CCHP systems. This study proposes a new approach to improve the overall efficiency of CCFP systems and to compute optimal design parameters in order to assist decision makers to identify the best geometrical configuration. A multi-objective optimization formulation of a solar-assisted CCHP system was adopted to maximize the net power and exergy efficiency and to minimize the CO\({}_{2}\) emission using the greywolf optimization technique. In addition, the effects of the decision variables on the objective functions were analysed. The proposed optimization approach yielded 100 set of Pareto optimal solutions which would serve as options for the decision maker when making a selection to choose from when seeking to improve the performance of a solar-assisted CCHP system. It also yielded higher exergy efficiency and lower CO\({}_{2}\) emission values when compared with a similar study. The results obtained indicate that a system with high net power output does not necessarily translate to a highly efficient system. Additionally, minimal CO\({}_{2}\) emissions were recorded for a system with low compression ratio, low combustion chamber inlet temperature and high inlet turbine temperature. This study demonstrates that the proposed approach is potentially suitable for the optimization of a solar-assisted CCHP system.  
tri-generation systems; CCHP; greywolf optimization; solar photovoltaic thermal collectors; net power; exergy efficiency; CO\({}_{2}\) emission