Miracle-dz/UniFAR-FTUs huggingface dataset:
Lifestyle and Spiritual Practices of Generation Z

Lifestyle reflects how a person spends his time in daily routine and life. A lifestyle which does not adhere to spiritual values may compromise a person’s well-being such as engaging in illegal street racing, free sex and gangsterism. This research aimed to identify the lifestyle activities of Generation Z, study their spiritual practices and analyze the relationship between the lifestyle activities and spiritual practices among Gen Z. This research is designed as a survey study. The main research instrument is questionnaire. Respondents are selected by stratified random sampling involving 673 Malaysian adolescents. The results showed that Gen Z are very concerned with personal hygiene. The spiritual practices most observed by Gen Z are solah, fasting, doa and being grateful. The research found that there is a significant relationship between lifestyle activities and spiritual practices among Gen Z. Spiritual practices have a positive impact on Gen Z’s lifestyle and well-being.
Automatic optical inspection method and automatic optical inspection equipment

The invention relates to an automatic optical inspection method and automatic optical inspection equipment. The automatic optical inspection method comprises the following steps of: colored light projection step which comprises the process of uniformly projecting three primary colors of light on an objected to be inspected to form images with different colors; obtaining the gray scale information corresponding to different areas of the images and then generating an automatic optical inspection standard image; and carrying out contrast inspection on the automatic optical inspection standard image with a prestored reference image. The method and the equipment have the beneficial effects that as the grey scale information of the images is only required to be processed, the data quantity and the processing difficulty of an image processing unit and a statistical analysis unit are reduced to facilitate the improvement on data collection reliability, precision, repeatability and speed; and the requirements on the inspection equipment are reduced, and the investment cost of the inspection equipment is also reduced.
Preemptive Fault Tolerance in DDS based Distributed System using Application Migration

: Software availability is the main concern of distributed systems regardless of design and framework. Faults are inevitable to any system and system should continue to function even in presence of these faults. Fault tolerance (FT) techniques should make the system fault tolerant by detecting and handling these faults. This paper introduces the technique of proactively anticipating the possible fault and then avoiding that fault by application migration. The possible fault is predicted through sudden or unusual utilization of CPU, RAM, fan speed or CPU temperature. Whenever CPU, RAM, fan speed or temperature breaches the permissible limits of any machine or an alert is generated based on historical data analysis; system takes the necessary steps to redistribute the application load based on software or hardware analytics. The proposed solution has proved to be more efficient than recovery from failure via traditional reactive FT mechanisms such as checkpoint/restart. The use of data distribution service (DDS) as communication middleware has helped in convenient state transfer and state maintenance of migrating application.
Retinal image segmentation using double-scale non-linear thresholding on vessel support regions

Retinal vessel segmentation is a critical indicator of diagnosis, screening, and treatment of cardiovascular and ophthalmologic diseases. Due to the fact that the retinal vessels usually have some tiny structures and blurred boundaries, especially with remarkable noises, it is difficult to correctly segment the vascular networks. In this study, the authors propose a double-scale non-linear thresholding method based on vessel support regions. First, the double-scale filtering method is applied to enhance the contrast between the foreground vascular and the background stuffs. Second, they segment the fine and coarse vessels by the corresponding adaptive local thresholding and fixed-ratio thresholding method. Finally, they obtain the binary segmentation by fusion of fine and coarse vessels. Experiments are conducted on the publicly available DRIVE and STARE datasets, which show the effectiveness of the proposed method on retinal vessel segmentation.
Short Test Summarization on the Comment Stream of Social Networks

Present days the prominence of interpersonal interaction administrations has expanded rapidly, so the amount of remarks can increment at a high rate instantly after a social message is distributed. so the quantity of remarks can raise at a high rate instantly after a social message is distributed. The clients of the social destinations dependably need to get a brief comprehension of a remark stream without perusing the entire remark list. With a specific end goal to bolster continuous short content outline of remark streams in interpersonal organizations, here proposed another rundown framework called RISTS. The clients of the social locales dependably craving to get a brief comprehension of a remark stream without perusing the entire remark list. So this framework endeavors to gathering remarks with comparable substance together and produce a compact conclusion outline for the message. Since various clients can ask for the outline at any minute, existing grouping strategies can't be straightforwardly connected in light of the fact that they can't meet the constant need of such application. So this remark stream outline issue is displayed as incremental bunching issue. This methodology can incrementally update grouping results with most recent approaching remarks continuously. Subsequently representation interface is created that help clients to quickly get a diagram outline.
ADABOOST Ensemble Algorithms for Breast Cancer Classification

With advances in technologies, different tumor features have been collected for Breast Cancer (BC) diagnosis. The process of dealing with large data set suffers some challenges which include high storage capacity and time required for accessing and processing. The objective of this paper is to classify BC based on the extracted tumor features and to develop an ADABOOST ensemble Model to extract useful information and diagnose the tumor. In this research work, both homogeneous and heterogeneous ensemble classifiers (combining two different classifiers together) were implemented, and Synthetic Minority Over-Sampling Technique (SMOTE) data mining pre-processing is used to deal with the class imbalance problem and noise in the dataset. In this paper, the proposed method involve two steps. The first step employs SMOTE to reduce the effect of data imbalance in the dataset. The second step involves classifying using decision algorithms (ADTree, CART, REPTree and Random Forest), Naive Bayes and their Ensembles. The experiment was implemented on WEKA Explore (Weka 3.6). Experimental results show that ADABOOST-Random forest classifies better than other classification algorithms with 82.52% accuracy, followed by Random Forest-CART with 72.73% accuracy while Naive Bayes classification is the lowest with 35.70% accuracy.
HotStrokes: Word-Gesture Shortcuts on a Trackpad

Expert interaction techniques like hotkeys are efficient, but poorly adopted because they are hard to learn. HotStrokes removes the need for learning arbitrary mappings of commands to hotkeys. A user enters a HotStroke by holding a modifier key, then gesture typing a command name on a laptop trackpad as if on an imaginary virtual keyboard. The gestures are recognized using an adaptation of the SHARK2 algorithm with a new spatial model and a refined method for dynamic suggestions. A controlled experiment shows HotStrokes effectively augments the existing "menu and hotkey" command activation paradigm. Results show the method is efficient by reducing command activation time by 43% compared to linear menus. The method is also easy to learn with a high adoption rate, replacing 91% of linear menu usage. Finally, combining linear menus, hotkeys, and HotStrokes leads to 24% faster command activation overall.
All Too Human: Confict and Common Ground in Interdisciplinary Research and Complex Problem Solving.

The identification of conflict and development of common ground, important steps in the interdisciplinary research process, become challenging when applied to solving complex real-world problems that involve opposing interest groups, especially those whose members do not possess academic or interdisciplinary training. This article examines psycho-social mechanisms that can complicate the interdisciplinary process in solving such problems, using attempts to solve the problem of anthropogenic climate change to exemplify the situation. Understanding the mechanisms of conflict as well as strategies of conflict resolution can improve the interdisciplinary research process in its application to complex real-world problems.
Flotation and Tailing Discarding of Copper Cobalt Sulfide Ores Based on the Process Mineralogy Characteristics

The mineral composition of copper–cobalt ores is more complex than that of copper sulfides, and it is also difficult to discard tailing efficiently in primary flotation for the fine-grained disseminated of ore. In this work, a mineral liberation analyzer (MLA) was employed to study the characteristics of minerals. As a significant mineralogical characteristic, the liberation degree of useful mineral aggregates was determined after grinding, and a correlation was established between the ore grinding size and mineralogical characteristics. The results showed that the adopted ore occurred in sulfide form. However, the particle size of the mineral’s monomer was fine grained, whereas its aggregate was coarse. The sulfide mineral aggregate obtained after primary grinding was selected as the recovery object, and its mineralogical characteristics, such as liberation degree and particle size, were investigated to promote total recovery in primary flotation. The copper–cobalt sulfide concentration was obtained at the following optimal conditions: the grinding size of −0.074 mm (65%), the aggregate’s liberation degree of 67%, a collector dosage of 50 g·t−1, a collector combination of 35% aerofloat + 65% butyl xanthate, a pH of 8.5, and 2# oil (a terpineol type foaming agent) dosage of 60 g·t−1. The recovered rough Cu and Co concentrates were 89.45% and 88.03%, respectively. Moreover, the grades of Cu and Co were 13.4% and 4.81%, respectively, with 85.07% of the ore weight discarded as tailing. The consideration of sulfide aggregates instead of singeral minerals mineralogy characters in primary grinding and primary flotation provides an effective theoretical guide for the sorting of sulfide minerals and reduction in the power consumption of grinding.
Topological stability of solenoidal automorphisms

In [10] A. Morimoto proved that every topologically stable homeomorphism of a compact manifold M has the pseudo-orbit tracing property in the case dim (M) ≥ 2. Further, in studying relation between the topological stability and other stability of diffeomorphisms, he showed the following Theorem A. Let Rr be the r-dimensional vector group and φ be a group automorphism of Rr .
De novo chromosome-level genome assembly of Chinese walnut (Juglans cathayensis Dode)

Chinese walnut (Juglans cathayensis Dode), is a diploid, woody species native to China. It has 16 chromosomes (2n =2x= 32), as do all members of its genus and most members of its family (Juglandaceae). Although high-quality sequence data and reference genomes are available for several Juglans species, our goal was to produce a de novo, chromosome-level assembly of the Chinese walnut genome to gain insights into the species’ evolution and biology. Our assembly was based on Nanopore long reads and chromosome conformation capture (Hi-C) data. The ﬁnal assembly showed a contig N50 size of 6.49 Mb and a scaﬀold N50 size of 36.1 Mb. The ﬁnal genome size of Chinese walnut was estimated to be 548 Mb. The sixteen scaﬀolds of the assembly anchored 99 % of the Chinese walnut genome. The assembly of the gene space (BUSCO) was 92.0 %. We annotated 29,032 protein coding genes with a mean of 6 exons per gene. We detected 2,993 non-coding RNA in the genome. A phylogenetic analysis based on 552 single-copy orthologs indicated that Chinese walnut close relative to Persian walnut (J. regia). The collinearity analysis showed that two whole genome duplication (WGD) events in J. cathayensis and J. regia from a common ancestor. Comparative genome analysis of J. cathayensis versus J. regia showed that 399 and 1,528 gene families were expanded and contracted respectively in the Chinese walnut genome. This J. cathayensis genome should be a useful resource for study of the evolution, breeding, and genetic variation in walnuts (Juglans).
Unconstraint 2-Level Cost Optimization Coding for Signal Processing

Evolution of new technologies has lead to the development of new devices, exchanging data over a diverse network area. Diversity in the propagation model has given diversity in the interference and has made the estimation algorithm limited to certain interference only. However, the increase in the propagation model, the co-channel interferences are increasing rapidly. In the estimation of such interference, recursive filters were proposed with the objective of lower complexity and faster convergence. Recursive B-spline approximation (RBA) is used as an optimal solution in this approach. An time shift kalman filtration (KF) approach to optimize the RBA using weighted least square (WLS) develops the objective of state stabilization in this approach. However, dynamic interference scenario in the propagation model, leads to a large convergence overhead and the bounded cost function constraint the estimation to bounded limits. To develop a unbounded estimation approach, in this paper, a new 2-Level unconstraint estimation approach for Kalman filter stabilization for RBA is proposed. The method defines a open bound to the signal estimation for faster convergence with higher estimation accuracy.
Practical Detection of Click Spams Using Efficient Classification-Based Algorithms

— Most of today’s Internet services utilize user feedback (e.g. clicks) to improve the quality of their services. For example, search engines use click information as a key factor in document ranking. As a result, some websites cheat to get a higher rank by fraudulently absorbing clicks to their pages. This phenomenon, known as “Click Spam”, is initiated by programs called “Click Bot”. The problem of distinguishing bot-generated traffic from the user traffic is critical for the viability of Internet services, like search engines. In this paper, we propose a novel classification-based system to effectively identify fraudulent clicks in a practical manner. We first model user sessions with three different levels of features, i.e. session-based, user-based and IP-based features. Then, we classify sessions with two different methods: a one-class and a two-class classification that both work based on the well-known K-Nearest Neighbor algorithm. Finally, we analyze our methods with the real log of a Persian search engine. Experimental results show that the proposed algorithms can detect fraudulent clicks with a precision of up to 96% which outperform the previous works by more than 5%.
Dynamic Model of Collaboration in Multi-Agent System Based on Evolutionary Game Theory

Multi-agent collaboration is greatly important in order to reduce the frequency of errors in message communication and enhance the consistency of exchanging information. This study explores the process of evolutionary decision and stable strategies among multi-agent systems, including followers, leaders, and loners, involved in collaboration based on evolutionary game theory (EGT). The main elements that affected the strategies are discussed, and a 3D evolution model is established. The evolutionary stability strategy (ESS) and stable conditions were analyzed subsequently. Numerical simulation results were obtained through MATLAB simulation, and they manifested that leaders play an important role in exchanging information with other agents, accepting agents’ state information, and sending messages to agents. Then, with the positivity of receiving and feeding back messages for followers, implementing message communication is profitable for the system, and the high positivity can accelerate the exchange of information. At the behavior level, reducing costs can strengthen the punishment of impeding the exchange of information and improve the positivity of collaboration to facilitate the evolutionary convergence toward the ideal state. Finally, the EGT results revealed that the possibility of collaboration between loners and others is improved, and the rewards are increased, thereby promoting the implementation of message communication that encourages leaders to send all messages, improve the feedback positivity of followers, and reduce the hindering degree of loners.
Two-Stage Integrated Electricity and Heat Market Clearing With Energy Stations

Integrated energy systems (IESs) provide a synergistic supply of electricity and heat, which offers a new approach for district heating. However, the operational risk of IESs increases continuously as the extent of renewable energy source (RES) penetration continues to increase. This condition negatively impacts the benefits of IESs to the participants in the integrated energy market (IEM) and increases the costs of the system. This paper addresses these issues by proposing a two-stage stochastic programming model that considers RES penetration for IESs operated independently of electricity grids (i.e., islanded IESs). Then, a two-stage clearing model of the IEM is established, and a market settlement process is designed. The simulation results demonstrate that the two-stage clearing model of the IEM can effectively alleviate the operational risk associated with high RES penetration by allowing market participants to make timely adjustments corresponding to their interests according to changes in RES generation.
Modeling of Pneumatic Melt Drawing of Poly-l-lactide Fibers in the Laval Nozzle

An air-drawing model of poly-l-lactide melt under a supersonic air jet in the Laval nozzle is presented. The aerodynamic fields are computed using the k–ω model. The pneumatic process is considered based on the mathematical model of melt spinning in single-, thin-filament approximation. Simultaneous acceleration of the air and the melt within the nozzle leads to fast attenuation of the filament. Air velocity dominates velocity of the filament and results in continual air-drawing on the entire spinning line. Oriented crystallization and nonlinear viscoelasticity effects under fast uniaxial elongation of the polymer melt are considered. The filament velocity at the collector increases significantly with increasing air compression, from the values typical for high-speed melt spinning up to values by two folds higher. The increase in filament velocity is limited by the effects of online oriented crystallization at higher air compressions. Influence of the inlet air compression, melt extrusion temperature and .
Social capital and innovativeness of social enterprises: opportunity-motivation-ability and knowledge creation as mediators

ABSTRACT This study contributes to an increased understanding of the role of opportunity-motivation-ability factors and knowledge creation in linking social capital and firm innovativeness. A pre-tested and pilot tested survey questionnaire was used to collect data from 112 managerial-level employees of Australian social enterprises. Structural equation modeling results confirmed the mediation effects of opportunity-motivation-ability factors and knowledge creation. Opportunity-motivation-ability factors interact with each other in their effect on knowledge creation leading to innovativeness. Results further support the importance of cognitive social capital for innovativeness. This study also extends the innovativeness concept into a new, previously overlooked application area, the Australian social enterprise context. Study findings suggest social enterprise managers to create more opportunities to knowledge exchange and reinforce shared vision to maintain a higher innovativeness. The future studies can confirm the study results with larger samples and test the moderation effect of social mission on the relationships established in this study.
Mapping the Thermal Structure of Southern Africa From Curie Depth Estimates Based on Wavelet Analysis of Magnetic Data With Uncertainties

Surface heat flow provides essential information on the thermal state and thickness of the lithosphere. Southern Africa is a mosaic of the best‐preserved and exposed crustal blocks, assembled in the early late Archean and then modified by a series of major tectono‐thermal events, both of Precambrian and Phanerozoic. Understanding the thermal and compositional structure of the southern African lithosphere provides crucial information for the actual causes, processes of lithospheric stability, and modification. Curie depth, interpreted as the depth to 580°C, provides a valuable constraint on the thermal structure of the lithosphere. Due to the sparse distribution of surface heat flow data, we examine the degree to which the thermal structure of the crust can be constrained from Curie depth estimates in southern Africa. We provide a Curie depth map for southern Africa (obtained from the inversion of magnetic anomaly data via power spectral methods and wavelet analysis) alongside with a heat flow map (based on the previous Curie depth estimates), both equipped with uncertainties via a Bayesian approach. Opposed to other cratonic regions, the observation of a shallow Curie depths and low heat flow over the Kaapvaal Craton suggests a thermochemical reworking of the cratonic lithosphere in this region. Furthermore, a comparison with a model for the Moho depth reveals significant variations of the Curie depth, which may be located below or above the Moho in large regions. Both observations indicate that in certain regions magnetic anomaly based Curie depth estimates may reflect a compositional rather than a temperature controlled constraint.
Automated Localization of a Mobile Construction Robot with an External Measurement Device

The localization of a robot is a crucial part of any task that involves the mobile manipulation of objects. The precise repositioning of a mobile robot within the workspace is particularly important for on-site construction in situations where the operating area is much larger than the reach of the robot arm. This research presents a localization method utilizing a generic surveying and measurement device – a robotic total station. The localization of the mobile robot in reference to the total station is investigated through the positioning of a reflector prism, mounted on the robot’s end-effector, at different known locations in robot’s coordinate frame. Through this localization method, the opportunity to remove the reliance on fixed reference points is tested in a largescale outdoor experiment, which would alleviate the need for a full enclosure around the mobile robot to help constrain its pose.