Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Stream Clustering Techniques, Applications, and Models: Comparative Analysis and Discussion

Data growth in today’s world is exponential, many applications generate huge amount of data streams at very high speed such as smart grids, sensor networks, video surveillance, financial systems, medical science data, web click streams, network data, etc. In the case of traditional data mining, the data set is generally static in nature and available many times for processing and analysis. However, data stream mining has to satisfy constraints related to real-time response, bounded and limited memory, single-pass, and concept-drift detection. The main problem is identifying the hidden pattern and knowledge for understanding the context for identifying trends from continuous data streams. In this paper, various data stream methods and algorithms are reviewed and evaluated on standard synthetic data streams and real-life data streams. Density-micro clustering and density-grid-based clustering algorithms are discussed and comparative analysis in terms of various internal and external clustering evaluation methods is performed. It was observed that a single algorithm cannot satisfy all the performance measures. The performance of these data stream clustering algorithms is domain-specific and requires many parameters for density and noise thresholds.
Process Mining Concepts for Discovering User Behavioral Patterns in Instrumented Software

Process Mining is a technique for discovering “in-use” processes from traces emitted to event logs. Researchers have recently explored applying this technique to documenting processes discovered in software applications. However, the requirements for emitting events to support Process Mining against software applications have not been well documented. Furthermore, the linking of end-user intentional behavior to software quality as demonstrated in the discovered processes has not been well articulated. After evaluating the literature, this thesis suggested focusing on user goals and actual, in-use processes as an input to an Agile software development life cycle in order to improve software quality. It also provided suggestions for instrumenting software applications to support Process Mining techniques. PROCESS MINING CONCEPTS FOR SOFTWARE APPLICATIONS 3 Acknowledgements The author gratefully thanks his advisor, Kevin Pyatt, for his patience and guidance in reviewing and providing improvements to this thesis. The author also thanks his wife, Shawn, for her proofreading, suggestions, and being a sounding board for ideas and rants. Her love and support were instrumental in winding this project towards its conclusion. Finally, the author thanks his parents for all the assistance they have provided over the years. They have served as inspirations for achieving goals in life, and for demonstrating that all individuals are worthy of respect even when the majority may wish to relegate them to obscurity. PROCESS MINING CONCEPTS FOR SOFTWARE APPLICATIONS 4 Table of
Ubiquitin-specific peptidase 22 promotes proliferation and metastasis in human colon cancer

Colon cancer is one of the most common malignant tumors in the world; however, the mechanism underlying the progression of colon cancer remains unclear. In the present study, the expression of ubiquitin-specific peptidase 22 (USP22) in paraffin sections of human colon cancer tissues and normal colon tissues were examined using immunohistochemistry. The human colon cancer cell lines HCT116 and HT29 were used for USP22 knockdown experiments, and functional assays were performed. The results demonstrated that compared with normal colon tissues, human colon cancer tissues exhibited upregulated expression of USP22 and this was associated with tumor lymph node metastasis and tumor stage in colon cancer tissues. In addition, upregulated expression of USP22 was significantly correlated with both lower relapse-free survival and lower overall survival rates in patients with colon cancer. When USP22 was silenced in colon cancer cell lines, this resulted in a decrease in cell proliferation and metastatic behaviors. Furthermore, Bmi-1 and Cyclin D2 were found to be positively regulated by USP22, which may have mediated the tumorigenic effects of USP22 in human colon cancer. The results of the present study may have significant implications for examining the underlying mechanisms of cancer development and the potential development of cancer therapeutics.
WSN Integrated Authentication Schemes Based on Internet of Things

The leader of the new generation of technology, namely the Internet of Things (IoT), is now already an indispensable part of many people’s lives. In this research, we have analyzed the main communication models of IoT in terms of functional conformity and classified those models into two kinds. Then, for each of the two kinds, we have developed a new generalized model that is applicable in practically every possible case. Our first new model is to be applied in most common network environments where users directly connect to the authentication server, whereas the second new model is most applicable when users connect to some specified devices instead of a server. Besides the couple of new communication models we have just developed, in this paper we shall also present some integrated security authentication schemes that we have designed. Through some thorough security analyses, we have proven that our new schemes can resist a collection of attacks including the replay attack, privileged insider attack, stolen verifier attack, stolen smart card and smart card breach attack, impersonation, as well as the offline password guessing attack. In addition to the high security level, our new schemes also provide user anonymity with the communication efficiency unaffected by the security protection. On top of everything, our major concern and contribution is for every member of the worldwide IoT user community to enjoy the conveniences the industry 4.0 technologies bring without loss of privacy and personal interests.
Constraint breeding during on-line incremental learning

An evolutionary algorithm for simultaneously inducing and weighting phonological constraints (Winnow-MaxEnt-Subtree Breeder) is described, analyzed, and illustrated. Implementing weights as sub-population sizes, re-production with selection executes a new variant of Winnow (Littlestone, 1988), which is shown to converge. A ﬂexible constraint schema, based on the same prosodic and au-tosegmental trees used in representations, is described, together with algorithms for mutation and recombination (mating). The al-gorithm is applied to explaining abrupt learning curves, and predicts an empirical connection between abruptness and language-particularity.
Patient-generated health data management and quality challenges in remote patient monitoring

Abstract Background Patient-Generated Health Data (PGHD) in remote monitoring programs is a promising source of precise, personalized data, encouraged by expanding growth in the health technologies market. However, PGHD utilization in clinical settings is low. One of the critical challenges that impedes confident clinical use of PGHD is that these data are not managed according to any recognized approach for data quality assurance. Objective This article aims to identify the PGHD management and quality challenges that such an approach must address, as these are expressed by key PGHD stakeholder groups. Materials and Methods In-depth interviews were conducted with 20 experts who have experience in the use of PGHD in remote patient monitoring, including: healthcare providers, health information professionals within clinical settings, and commercial providers of remote monitoring solutions. Participants were asked to describe PGHD management processes in the remote monitoring programs in which they are involved, and to express their perspectives on PGHD quality challenges during the data management stages. Results The remote monitoring programs in the study did not follow clear PGHD management or quality assurance approach. Participants were not fully aware of all the considerations of PGHD quality. Digital health literacy, wearable accuracy, difficulty in data interpretation, and lack of PGHD integration with electronic medical record systems were among the key challenges identified that impact PGHD quality. Conclusion Co-development of PGHD quality guidelines with relevant stakeholders, including patients, is needed to ensure that quality remote monitoring data from wearables is available for use in more precise and personalized patient care.
Using The Neural Network to Track Maximum Point of Photovoltaic Cells Power and Improve Efficiency In Partial Shade Conditions

Using solar energy has been increasing in the last decade. This has increased researcher’s motivation to investigate on solar cells and improve terms of its use. Such modern methods in this field are to use smart methods to operate and track power maximum point. In this article, the smart method based on the neural network to track power maximum point even in shade conditions is used. Considering partial shade effect and maximum power point tracking in these conditions, using neural network helps to improve cell operation and decrease uncertainty effect in the cell. This method simulation has been done in MATLAB software.
The complementary effect of rs1042522 in TP53 and rs1805007 in MC1R is associated with an elevated risk of cutaneous melanoma in Latvian population

Genetic factors serve important roles in melanoma susceptibility. Although much genetic variation has been associated with cutaneous melanoma (CM), little is known about the interactions between genetic variants. The current study investigated the joint effect of rs1042522 in the tumour protein 53 (TP53) gene, rs2279744 in the murine double minute-2 (MDM2) gene and several single nucleotide polymorphisms (SNPs) in the melanocortin 1 receptor (MC1R) gene. All of these genes are interconnected in a single signalling pathway that regulates pigmentation. The current study included 479 individuals, of which, 255 were patients with CM and 224 were controls from the Latvian population. Multifaceted analyses of potential interactions between SNPs were performed, whilst taking into account the pigmentation phenotypes of individuals and tumour characteristics (Breslow thickness and ulceration). Univariate analyses revealed a borderline significant association between rs1042522 in the TP53 gene and CM risk. The results also confirmed a known association with rs1805007 in the MC1R gene. The rs1042522 was also selected as a CM risk factor in multivariate models, suggesting an effect that is independent from and complementary to that of rs1805007. The results indicated that these SNPs need to be taken into account when determining melanoma risk. A strong association between CM and red hair was identified for rs1805007, and rs1805008 in the MC1R gene was mainly associated with red hair. An association was also determined between rs2279744 in the MDM2 gene and brown eye colour. No convincing associations were identified between the analysed SNPs and Breslow thickness of tumours or ulcerations.
Exemestane leads to hormone-associated ascites in female hamsters with experimental metabolic syndrome

Aim: During the study of the aromatase inhibitors effect on metabolic disorders, it was found that exemestane significantly caused ascites. This part of pre-clinical study aimed to investigate the potential dysregulatory effect of exemestan on adrenal synthesis of hormones with miniralocorticoid activity under the conditions of experimental
Introducing Usage-Based Encryption for a Secure and Versatile Access Control Scheme of Electronic Health Records on Cloud

In this study, we introduce Usage-Based Encryption (UBE) approach for a secure, efficient, ubiquitous and versatile management of Electronic Health Records (EHRs) on cloud. The primordial feature lies in delegating the fundamental security guidelines and procedures to the patient in terms of encryption, access control and digital signatures. In contrast with other frequently used approaches, the proposed scheme grants the patient enhanced independence from cloud providers’ policies and thus, renders increased administrative authority while sustaining a highly flexible and resourceful configuration. A comprehensive scheme is painstakingly detailed to encompass all tangible situations pertaining to a highly effective control of the EHR in a platform-free sphere. As a matter of fact, encryption and hashing modi operandi are scrupulously and relevantly fixed on to guarantee Confidentiality, Integrity and Availability (CIA). Furthermore, privileges and revocation of access are discussed in their minutiae from a usage perspective to provide patients broader maneuverability of their health records prior to housing them on clouds.
Comparison of overall component alignment and functional outcome between navigation and conventional total knee arthroplasty

Aim: of the study was to compare the functional outcome in patients undergoing navigation and conventional total knee replacement. secondly to compare the component alignment in patients undergoing navigation and conventional Total Knee Replacement. Materials and methods: Total 80 patients were included in study out of which 40 patients were in each group. All the surgeries were done by single surgeon and subvastus approach was used for all the total knee replacements. Pre-operative functional assessment was done by KSS score14. Preoperative radiological grading of osteoarthritis was done using AHL back. Post operatively all patients were followed upto 1,3 and 6 months and at the end of 6 months radiological assessment of the components was done by measuring Alpha, beta, gamma and sigma angles. Conclusion: Navigation TKR significantly improves the alignment of both femoral and tibial components when compared with the conventional TKR. However there was no significant difference in functional outcome between the two methods. Probably a long term study might highlight on if navigation has a role in improving the longevity of the implant.
Heart Rate Variability Biofeedback Improves Sports Performance in an Elite Female Athlete

Introduction and Purpose: Rigorous training of elite athletes can lead to nonfunctional overreaching (NFOR) andovertraining (OT), both ofwhich decrease performance and increase the risk of injury. Heart rate variability (HRV) is a measure of autonomic nervous system balance. Reductions in HRV are associatedwith NFOR and OT. Breath-based biofeedback increases HRV through activation of the baroreceptor reflex. Purpose: This case study explored the impact of breath-based HRV biofeedback (HRV-BF) training on daily resting HRV values of a female triathlete and the association between daily HRV with subjective performance indicators of workout quality and amount of postworkout energy. Methods: A 24-year-old female triathlete completed an 8-week A-B repeated-measures study—A: baseline; 4 weeks and B: intervention HRV-BF training; 4 weeks. The subject recorded daily resting HRV for 120 seconds, completed regular daily training, and measured workout performance and postworkout energy levels on a 0 to 10 scale. During B, the subject added 15minutes of HRVBF 5 times per week. Results: With HRV-BF, median HRV level increased (A: 137; B: 191) and the interquartile band narrowed (A: 83–184; B: 142–201), suggesting higher HRVwith less variability. The subject hadmore days at highest readiness (A: 35%; B: 62%). Median values for reports of workout performance and postworkout energy increased. Conclusions: This study found that, for this subject, 15 minutes of HRV-BF, 5 times per week, was associatedwith increased HRV and improved subjective workout performance. Further research exploring HRV measures and biofeedback to inform athletic performance is warranted. (Cardiopulm Phys Ther J. 2020; 31:123–132)
SEGMENTATION OF 3D PHOTOGRAMMETRIC POINT CLOUD FOR 3D BUILDING MODELING

Abstract. 3D city modeling has become important over the last decades as these models are being used in different studies including, energy evaluation, visibility analysis, 3D cadastre, urban planning, change detection, disaster management, etc. Segmentation and classification of photogrammetric or LiDAR data is important for 3D city models as these are the main data sources, and, these tasks are challenging due to their complexity. This study presents research in progress, which focuses on the segmentation and classification of 3D point clouds and orthoimages to generate 3D urban models. The aim is to classify photogrammetric-based point clouds (> 30 pts/sqm) in combination with aerial RGB orthoimages (~ 10 cm, RGB image) in order to name buildings, ground level objects (GLOs), trees, grass areas, and other regions. If on the one hand the classification of aerial orthoimages is foreseen to be a fast approach to get classes and then transfer them from the image to the point cloud space, on the other hand, segmenting a point cloud is expected to be much more time consuming but to provide significant segments from the analyzed scene. For this reason, the proposed method combines segmentation methods on the two geoinformation in order to achieve better results.
AeroMRP: A Multipath Reliable Transport Protocol for Aeronautical Ad Hoc Networks

In order to support Internet of Things, an aeronautical ad hoc network (AANET) has been proposed to solve the problem of air information isolated island. AANET is a special type of heterogeneous ad hoc network between commercial aircraft to share data and in-flight Internet access. Today’s civil airliners are typically equipped with multiple advanced network interfaces, which can form multiple independent communication paths between the source and the destination nodes in AANETs. Thus, users expect to utilize multiple networking interfaces of airliners simultaneously to support data transfer services. In this paper, we present a multipath reliable transport protocol for AANETs, called AeroMRP, which exploits path diversity provided by heterogeneous aeronautical networks. AeroMRP takes advantage of raptor codes to restore from packet loss in the aeronautical network environments while reducing the impact of the head-of-line blocking issue in the networks with multiple paths. A redundancy rate selection algorithm is adopted to determine the redundancy on the fly by considering the characteristics of the target applications and the time-varying aeronautical networks. Moreover, AeroMRP implements feedback-based packet scheduling considering not only aeronautical network status but also the acknowledgment scheme in congestion control for better use of different paths. We evaluate the performance of AeroMRP by ns-3 under a variety of simulation scenarios. The simulations demonstrate that AeroMRP can provide efficient and reliable data transmission services in heterogeneous multipath AANETs.
Effect of Rising Temperature on Lyme Disease: Ixodes scapularis Population Dynamics and Borrelia burgdorferi Transmission and Prevalence

Warmer temperatures are expected to increase the incidence of Lyme disease through enhanced tick maturation rates and a longer season of transmission. In addition, there could be an increased risk of disease export because of infected mobile hosts, usually birds. A temperature-driven seasonal model of Borrelia burgdorferi (Lyme disease) transmission among four host types is constructed as a system of nonlinear ordinary differential equations. The model is developed and parametrized based on a collection of lab and field studies. The model is shown to produce biologically reasonable results for both the tick vector (Ixodes scapularis) and the hosts when compared to a different set of studies. The model is used to predict the response of Lyme disease risk to a mean annual temperature increase, based on current temperature cycles in Hanover, NH. Many of the risk measures suggested by the literature are shown to change with increased mean annual temperature. The most straightforward measure of disease risk is the abundance of infected questing ticks, averaged over a year. Compared to this measure, which is difficult and resource-intensive to track in the field, all other risk measures considered underestimate the rise of risk with rise in mean annual temperature. The measure coming closest was “degree days above zero. ” Disease prevalence in ticks and hosts showed less increase with rising temperature. Single field measurements at the height of transmission season did not show much change at all with rising temperature.
Cockroach Inspired Shelter Seeking for Flying Swarms of Robots

Division of Space Technology DEPARTMENT OF COMPUTER SCIENCE, ELECTRICAL AND SPACE ENGINEERING Master in Space Engineering Cockroach Inspired Shelter Seeking for Flying Swarms of Robots by Hamoon Shahbazi In computer science, the study of mimicking nature has given rise to Swarm Intelligence, a distributed system of autonomous agents interacting with each other to collectively perform intelligent tasks. This chapter investigates how groups of holonomic flying robots such as quad copters can seek shelter autonomously when encountering bad weather. In this context three alternative autonomous shelter seeking techniques that address the unsolved plateau-problem had to be implemented. The methods were inspired by cockroaches and hunting strategies observed in apex predators. Previous studies on cockroaches have provided facts about their behaviour and resulted in algorithms that can be used for robotic systems. This research builds on these previous studies by formulating three alternative techniques and carrying out a comprehensive analysis of their performance. Simulation results confirm a scalable system where swarms of flying robots successfully find shelters in 3-D environments.
A Case for 8 Bit Architectures

Many steganographers would agree that, had it not been for scatter/gather I/O, the refinement of robots might never have occurred. Given the current status of pseudorandom modalities, cryptographers famously desire the visualization of compilers, demonstrates the intuitive importance of machine learning. In this position paper, we explore a heuristic for vacuum tubes (YELK), which we use to confirm that link- level acknowledgements can be made large-scale, signed, and pervasive.