Miracle-dz/UniFAR-FTUs huggingface dataset:
Orthogonal software testing: Taguchi methods in software unit and subsystem testing

Suggests that, in order to detect and correct software defects as early as possible, identifying and generating more defect‐sensitive test cases for software unit and subsystem testing is one solution. Proposes an orthogonal software testing approach based on the quality optimization techniques, Taguchi methods. This orthogonal approach treats the input parameters of a software unit or subsystem as design factors in an orthogonal arrays, and stratifies input parameter domains into equivalent classes to form levels of factors. Describes how test cases are generated statistically for each trial of factorial orthogonal experiments. The adequacy of the generated test cases can be validated by examining testing coverage metrics. The results of test case executions can be analysed in order to find the sensibility of test cases for detecting defects, to generate more effective test cases in further testing, and to help locate and correct defects in the early stage of testing.
Ethanolic Extract of Ocimum sanctum Leaves Reduced Invasion and Matrix Metalloproteinase Activity of Head and Neck Cancer Cell Lines

Head and neck squamous cell carcinoma (HNSCC) has a yearly incidence of 600,000 cases worldwide with a low survival rate. Ocimum sanctum L. or Ocimum tenuiflorum L. (Holy basil; Tulsi in Hindi), is a traditional medicine herb that demonstrates numerous effects, including anti-oxidant, anti-microbial, and anti-tumor effects. The aim of this study was to evaluate the anti-invasive effect of O. sanctum leaf extract on HNSCC cell lines. Ethanolic extract of O. sanctum leaf (EEOS) was prepared and the phenolic compounds were identified using high-performance liquid chromatography-electrospray ionization-time of flight-mass spectrometry. Genetically-matched HNSCC cell lines derived from primary (HN30 and HN4) and metastatic sites (HN31 and HN12) from the same patient were used in this study. The EEOS cytotoxicity to the cell lines was determined using an MTT assay. The invasion and matrix metalloproteinase (MMP)-2 and -9 activity of EEOS-treated cells were tested using a modified Boyden chamber assay and zymography, respectively. We found that EEOS significantly inhibited the invasion and MMP-2 and MMP-9 activity of HN4 and HN12 cells, but not HN30 and HN31 cells. Rosmarinic acid, caffeic acid, and apigenin were detected in EEOS. Moreover, rosmarinic acid was found as the major phenolic compound. Therefore, EEOS exerted its anti-invasive effect on HNSCC cells by attenuating MMP activity.
Design of Miniaturization Microstrip Filter in L-Band

A curve of the relationship between the gaps of microstrip resonator and coupling coefficients is presented in this paper, which based on the study of small planar microstrip bandpass filter design theory and implementation. According to the curve, a small microstrip bandpass filter with 6.67% relative bandwidth in L-band is designed by Multi-zigzag line and capacitive loading technology. Compared to the similar hairpin line filters, the area of the filter designed in this paper is reduced by 64% with advantage of smaller size and more simple structure. The examples and results of a fifth-order Chebyshev responsible L-band bandpass filter are presented in the end of this paper.
The Mechanical Loads on the Low Back during Different Patient Handling Tasks

High prevalence rate of low back disorders (LBD) is found among nursing personnel. To get a more detailed knowledge concerning the risk factor in the health care sector, the working postures and the mechanical load of the low back were measured during nine commonly used patient handling tasks. Further the variation in the load between the different tasks was compared with the variation between subjects when they perform the same tasks. The study includes 10 female nurses with no special education or course in patient handling technique and a male stroke patient. The load during the different tasks were quantified from the net moment at L4/L5 joint calculated by use of a 3D biomechanical dynamic multi-segment model, the measured muscle activity (EMG) in erector spinae muscles and the kinematics of the low back. Significant differences in the mean values for all the dependent variable both between tasks and between subjects were found. The highest moment was found during the two tasks typically involving a lifting procedure of the whole bodyweight of the patient. High moment was however also found during tasks where the patient is “only” being repositioned in the bed. The position data measured for the low back are more difficult to interpret since no recommendations for limits are available in the literature. A high intersubject variation is found for all the outcome variables for a given task. This emphasizes the importance of an exposure assessment including individual measures. Otherwise, the risk for misclassification may be high and a detailed task description less effective for recommending prevention strategy.
Spatio‐temporal behaviour after an earthquake: a case study of Kawaguchi town, Japan

Purpose – The purpose of this paper is to provide a method to examine the differences in behaviour during a post‐quake period.Design/methodology/approach – Fieldwork and questionnaires were used to collect the households’ members’ movement behaviours after the 2004 Chuetsu Earthquake. In total, three study areas were selected in Kawaguchi town (Niigata Prefecture) in order to enhance how the visualisation process can provide support in better understanding the behaviour during evacuation and recovery process. For this purpose the Space‐Time‐Cube (STC) was used to represent and analyse residents’ movement paths over time.Findings – Differences appear in the spatio‐temporal paths of the three study areas, implying a connection between the geographical location and movement patterns. The city centre shows disorganized Spatio‐Temporal‐Patterns (STPs) during the first week of the recovery process, eventually becoming organized after the rescuers’ arrival. Moving towards the isolated areas of the town, a progre.
Network-Coding-Based Mutually Cooperative Transmission in Deep Space Communications

In deep space exploration, spacecrafts need to deliver large volume of time-insensitive scientific data to deep space station. However, power supply of spacecrafts is only from the solar energy and battery. That is to say, these spacecrafts are energy-limited. In order to reduce energy consumption, prolong the life of spacecrafts and send more data, the transmission protocol must be efficient and low-energy-waste. To achieve the aim, this paper proposes a network-coding-based mutually cooperative transmission protocol (NMCTP). Compared with the known protocols, i.e., COPE protocol and repeating transmission protocol, NMCTP can achieve higher diversity gain, and lower system outage probability.
30.2: Invited Paper: Advancements in Inkjet Printing for OLED Mass Production

Continuous improvements in inkjet printing of organic light emitting diode (OLED) displays have resulted in a number of recent demonstrations of uniform, mura-free TV-sized panels. These improvements combined with steady progress in solution OLED material performance, have allowed inkjet to become a realistic near term enabler of cost-effective mass production of large size OLED TVs. However, for inkjet to make the transition from R&D to mass production, a number of equipment challenges must be overcome, including achieving low particle contamination, maintaining the optimal process environment while preserving serviceability, and providing consistent, uniform, mura-free results with a wide process window. In this paper, the methodology (with respect to algorithms and process control) used in Kateeva's YIELDjet platform are described that lead to the uniform deposition of ink across an OLED display using inkjet printing, resulting in a highly uniform OLED emission with a wide process window.
The molten wood’s metal initial velocity variations effect on breaching simulation by MPS method

Series of MPS simulations have been conducted using two-dimensional geometry. The simulation was based on Sudha’s experiment (2018) about initial velocity variations on molten Wood’s Metal (WM). The molten WM would be flowed through nozzle with the diameter was 6 mm. It would impinge to the Woods Metal Plate (WMP) which 270 mm below the nozzle. The WMP diameter was 470 mm. The temperature of molten WM and WMP were set at 573 K and 300 K, respectively. The initial velocity of molten WM was varied at 0.327 m/s, 0.397 m/s, 0.498 m/s in the y-negative direction. The simulation was calculated by using 2D MPS with additional procedures such as heat transfer calculation and defining a new type of wall particle. The results showed some different spread patterns, leading edge and phase fraction change for each initial velocity. It can be concluded that with varying the initial velocity will affect on the radial spread pattern but not so much effect occurs on the phase volume fraction change.
Queueing and Traffic in Cellular Radio

A Cellular Radio system is analyzed from the communications traffic point of view. A cell within a given system is modeled by a multi-server service facility with or without the possibility of queueing some type of customers. Two types of arrivals are distinguished, corresponding to handoff calls (calls already in progress that enter the cell) and originating calls (calls initiated inside the cell). The queueing system used assumes Poisson distributed arrivals with different rates for the two types of customers. We initially assume, as is usually done for telephone communications, an exponential distribution for the service times of the customers. Due to mobility of the subscribers that can travel through several cells in the system, the channel occupancy time is in general different from the total call duration. Using both a simulation of a cellular system and an analytic model we offer evidence that a memory-less distribution may not be too unrealistic for the channel occupancy time. We derive some traffic policies that give a higher level of protection to handoff calls, and their influence on the other class of customers as well as on the overall traffic is analyzed. The first policies proposed have the advantage of simplicity and provide an efficient way of reducing the blocking probability of handoff calls while only slightly increasing the blocking probability of originating calls. The price paid is, however, a small decrease in the total carried traffic. Some more evolved traffic policies are then introduced that still decrease the blocking probability of handoff calls without much penalizing originating calls whose access to the system will only be slightly delayed. These more evolved policies provide the additional advantage of increasing the total carried traffic, while still providing a higher level of protection to handoff calls.
A decision-making model for Lean, Agile, Resilient and Green supply chain management

In modern business environments, an effective supply chain management (SCM) is crucial to business continuity. Competition between supply chains (SC) has replaced the traditional competition between companies. Lean, Agile, Resilient and Green (LARG) paradigms are advocated as the foundation of a competitive SCM. To make a supply chain more competitive, capable of responding to the demands of customers with agility and capable of responding effectively to unexpected disturbance, in conjugation with environmental responsibilities and the necessity to eliminate processes that add no value, companies must implement a set of LARG SCM practices and key performance indicators (KPI) to measure their influence on the SC performance. However, the selection of the best LARG SCM practices and KPIs is a complex problem, involving dependencies and feedbacks. This paper proposes an integrated LARG analytic network process (ANP) model to support decision-making in choosing the most appropriate practices and KPIs to be implemented by companies in an SC. To validate the model in an exploratory approach, a case study in an automaker supply chain is presented.
An Echo Sequence Profile Image Based Ship Target Classification Algorithm for Low-Resolution Radar

Ship target classification is of great significance in both military and civilian fields. We propose a ship target classification algorithm for low-resolution radars with echo sequence profile images. This algorithm can be realized in the following steps. First, we collect radar profile image data. We use five perspectives of a radar target, including target shape, Radar Cross Section (RCS), echo amplitude, motion attribute, and features of two-dimensional grayscale maps, to extract eight-dimensional feature vectors. The proposed algorithm uses the Support Vector Machine (SVM) as the classifier, and the parameters of the classifier are optimized by either grid search or the Particle Swarm Optimization (PSO) algorithm. The proposed algorithm is verified through real data classification tests.
Evaluations of An Algorithm for Large Multivariate Optimization

Many simulation-driven engineering and scientific problems require finding an optimum of a function with many variables. Such settings pose a challenge for standard algorithms due to the large search space which in turn can lead to poor final results. Therefore this paper proposes a new simplified approach in which the dimension of the problem is dynamically reduced during the search to formulate a problem of lower size (dimension) which is easier to solve. A main novelty of the algorithm is its simplicity. Numerical experiments show the potential of this approach.
The Welfare Consequences of Compound Risk

To avoid paternalism, behavioural welfare evaluations increasingly use information on preferences and beliefs of individuals from a “reference task,” such as a survey or experiment, to evaluate welfare gains and losses from decisions made in a context under study. This raises questions about the appropriateness of these preferences in the reference task for the decisions one aims to normatively evaluate. We propose that our beliefs about structural drivers of poor decisions, decisions that cause welfare losses, can guide the selection of an appropriate reference task for normative evaluation in many instances. We demonstrate this approach in the context of welfare evaluations of insurance choices with compound risk, where violations of the Reduction of Compound Lotteries axiom can lead to welfare losses. By using a standard risky lottery task, as well as a simple risk insurance task, we show that welfare losses do result from violations of that axiom when individuals make insurance decisions with compound risk. This is driven by excess purchase, particularly from individuals best characterized as Rank Dependent Utility decision-makers. JEL classification: D81, D60, D90, C90 ∗Department of Risk Management & Insurance and Center for the Economic Analysis of Risk, Robinson College of Business, Georgia State University, USA. Harrison is also affiliated with the School of Economics, University of Cape Town. E-mail: gharrison@gsu.edu †Department of Economics, Copenhagen Business School, Denmark. Email: jima.eco@cbs.dk ‡Department of Economics, Utrecht University. Morsink is also affiliated with the Development Economics Group, Wageningen University and the Center for the Economic Analysis of Risk, Georgia State University. Email: k.morsink@uu.nl §Center for the Economic Analysis of Risk, Robinson College of Business, Georgia State University, USA. Email: jiamin.ng@outlook.com ¶Department of Economics, Andrew Young School of Policy Studies, Georgia State University, USA. Email: jtswarthout@gmail.com
The Psychological Impact of COVID-19 on the General Population in Morocco

Introduction: Currently, we are going through an exceptional sanitary crisis due to the appearance of SARS-COV2, the containment being an act of social distancing is taken as a preventive measure to decrease the spread of the virus. It is undeniable that the COVID-19 pandemic affects not only physical health but also mental health and well-being. The objective of our study is to evaluate the impact of the virus in the general population in Morocco, including stress and sleep disorders. Methodology: To develop this work, we used an anonymous questionnaire based on, in addition to individual status and conditions, scales assessing stress and sleep. The PSS-10 (Cohen's Perceived Stress Scale) for perceived stress and ISI (C. Morin's Insomnia Severity Index) for sleep disorders were chosen. Results: We collected 1240 participants, the median age of our participants is 29 years (25-34), with a female predominance of 89.5%. Most of our participants at this stage would have already known someone who had not already contracted the virus with a percentage of 71.7%. Regarding the evaluation of perceived stress, 66% had moderate stress, 16% had mild stress and 13.70% had severe stress. For sleep, 34.7% would have had mild insomnia, 32.3% moderate insomnia, 9% severe insomnia and 24% would not have had insomnia. Female gender, being divorced, living in a rural area, and knowing someone close to you who has had the virus were found to be factors influencing perceived stress. For insomnia, being 18 to 29 years old and female increases the risk of insomnia. Conclusion: The assessment of perceived stress and sleep disturbances concluded that there was a clear impact of the pandemic on the lives of the general population in Morocco.
Growth and survival of spiny lobster, Panulirus homarus fed fresh food and formulated diet

To date, lobster aquaculture relies on fresh food for feeding; however, the availability of fresh food is limited and its excessive use causes environmental degradation. Therefore, formulated diet is required to establish sustainable lobster aquaculture. Concerning this issue, this study was carried out to assess the growth and survival of spiny lobster Panulirus homarus fed fresh food and formulated diet. The study was conducted in a completely randomized design (CRD) with 3 groups of treatments and 3 replicates for each treatment. Feeding experiment was performed in a flow-through water system using 9 fibre tanks, 4000 L in volume. Each tank was stocked with 40 lobsters, with initial weight of 78.08 ± 0.22 g. Each group of lobsters was fed with fresh food (A), formulated diet (pellet) (B) and a combination of pellet and fresh food (C). The fresh food was a mixture of fish, crabs, shrimp and small mussel (3:1:1:1). Feeding experiment was done for 15 weeks. Results of the experiment showed that the highest specific growth rate of lobster was obtained from lobsters fed with the combination of pellet and fresh food (0.52 ± 0.02 %/day) and the lowest growth was resulted from lobsters fed formulated diet (0.16 ± 0.03 %/day). In contrast, the highest survival was achieved in lobsters fed formulated diet (51.67%). Whereas the lowest survival was found in lobsters fed fresh food (10%). This study indicated that good growth of lobster was resulted from feeding with formulated diet combined with fresh food, while good survival was supported by feeding with formulated diet.
Unsupervised Approach for the Identification of the Predominant Site of Upper Airway Collapse in Obstructive Sleep Apnoea Patients Using Snore Signals

Knowledge regarding the site-of-collapse in the upper airway in obstructive sleep apnoea (OSA) has implications for treatment options and their outcomes. However, current methods to identify the site-of-collapse are not suitable for clinical practice due to the invasive nature, the time/cost of the tests and the inconsistency of the obstruction site identified with natural and drug-induced sleep. In this study, we adopted an unsupervised algorithm to identify the predominant site-of-collapse of the upper airway during natural sleep using nocturnal audio recordings. Nocturnal audio was recorded together with full-night polysomnography using a ceiling microphone. Various acoustic features of the snore signal during hypopnoea events were extracted. We developed a feature selection algorithm combining silhouette analysis with the Laplacian score algorithm to select the high performing features. A k-means clustering model was developed to form clusters using the features extracted from snore data and analyse the correlation between the clusters generated and the predominant site-of-collapse. Cluster analysis showed that the data tends to fit well in two clusters with a mean silhouette coefficient of 0.79 and with an accuracy of 68% for classifying tongue/non-tongue collapse. The results indicate a correlation between snoring and the predominant site-of-collapse. Therefore, it could potentially be used as a practical, non-invasive, low-cost diagnosis tool for improving the selection of appropriate therapy for OSA patients without any additional burden to the patients undergoing a sleep test.
Modelling and Implementation of a Knowledge Question-answering System for Product Quality Problem Based on Knowledge Graph

Aiming at the problem of difficulty in understanding the semantics of the problem in the traditional quality problem management system, the knowledge retrieval technology of product quality problem based on the knowledge graph is carried out. The process model for knowledge retrieval of quality problem based on semantic templates is constructed. A domain corpus is built, which consisting of thousands of quality problem handling records. The TF-IDF (Term Frequency-inverse Document Frequency) algorithm was used to extracted the vocabulary from the quality problem analysis reports. A natural language question semantic classification process model based on Naive Bayes classifier is established to improve the accuracy of semantic template matching. On the basis of theoretical study, a quality problem knowledge question-answering system-QQ-KQAS based on knowledge graph is developed, and the effectiveness of the proposed method is verified through examples.
Key-Point Interpolation: A Sparse Data Interpolation Algorithm based on B-splines

B-splines are widely used in the fields of reverse engineering and computer-aided design, due to their superior properties. Traditional B-spline surface interpolation algorithms usually assume regularity of the data distribution. In this paper, we introduce a novel B-spline surface interpolation algorithm: KPI, which can interpolate sparsely and non-uniformly distributed data points. As a two-stage algorithm, our method generates the dataset out of the sparse data using Kriging, and uses the proposed KPI (Key-Point Interpolation) method to generate the control points. Our algorithm can be extended to higher dimensional data interpolation, such as reconstructing dynamic surfaces. We apply the method to interpolating the temperature of Shanxi Province. The generated dynamic surface accurately interpolates the temperature data provided by the weather stations, and the preserved dynamic characteristics can be useful for meteorology studies.