Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study of Feature Clustering Analysis based on the Hidden Layer Representation of an Autoencoder

: Analysis of customer purchase behavior is an active research area. Several recent studies in this area have focused on detecting groups based on similar features from the available business data. One of the efficient approaches used for dividing all data into several groups with similar features is called clustering. Application of clustering to customer or item data can generate results that can help a company develop efficient marketing strategies. However, it is a non-trivial task to apply a general clustering method to a dataset with high dimensionality and sparsity owing to the difficulty of defining an appropriate similarity metric between the data samples. In this situation, one should reduce the dimensionality of data in advance. The autoencoder is a well-known model based on neural network, which can convert high-dimensional nonlinear data to low-dimensional expressions. In this research, we propose a method for clustering high-dimensional sparse data efficiently with deep learning method. The first step of our proposed method is to adopt SDAE for dimensionality reduction. The second step is to conduct a clustering analysis using the hidden layer expressions of SADE. The effectiveness and the usability of the proposed method are clarified through its application on real purchase history data.
Interface Improvement and Development of New Tools in the BobiSoft Software

In this thesis, the development of a new version of an analytical-based software named BobiSoft, for three-phase induction machine stator winding design, is presented. The purpose of this software is to aid and guide the (re)designing of high-quality and high-e ciency windings, being specially designed for the rewinding task. The software automatically designs 9 integer winding con gurations, but also allows the user to design free integer or fractional symmetric windings. It requires some basic information regarding the machine's stator geometry and winding as input data. The software then outputs relevant results which allow the user to quickly evaluate the computed solution. The main goal of this work is to improve this software to a high level of sophistication and innovation, creating new and important features for winding designing and project evaluation. Innovative tools have been developed to exploit as much as possible the available opportunities for winding optimization, leaving only a few possibilities for further improvements. In particular, the development of an iterative algorithm that searches for the best combination of di erent number of turns per coil and e ective coil pitch that minimizes the air-gap MMF harmonic content. In order to be fast, the algorithm was developed so it can be parallelized in the CPU or GPU. The speedup gain was huge. In the last part of this work, the software was tested and the results were quite good, proving that the developed features are correct. In addition, an ineld test was successfully conducted in order to evaluate the software's robustness and accuracy in a real situation.
Low-High Burst: A Double Potency Varying-RTT Based Full-Buffer Shrew Attack Model

The full-buffer Shrew (FB-Shrew) denial of service (DoS) attack is a variant of the classic Shrew attack that exploits the congestion control mechanism of transmission control protocol (TCP). Here, an attacker sends a high-rate burst of attack packets only after the router buffer is filled with TCP packets, causing the router to drop legitimate packets, and forcing the retransmission of TCP packets. As such, an FB-Shrew attack can cause maximum damage with minimum resources. In this paper, we challenge an assumption of constant round trip time adopted in the original FB-Shrew model. As a result, this model fails to achieve its expected attack effect. In response, we analyze the TCP congestion window and queue behaviors to develop two low-high burst models for maximizing the potency of the FB-Shrew attack. Model 1 is designed to achieve the attack effect expected of the original model. Then, the attack potency of Model 1 is enhanced by simply adjusting the starting time of the attack burst to form Model 2. Mode 1 only exploits the retransmission timeout (RTO) mechanism. Model 2 takes advantage of both the RTO mechanism and the fast retransmission mechanism. In this way, Model 2 further slows down the growth of the congestion window and extends the attack period. A combination of theoretical analyses and simulations are adopted to first validate the proper functioning and effectiveness of the two models for a standard network configuration, and then we assess their attack performances with variations in different network parameters. Our performance assessment demonstrates that one attack unit of Model 2 damages almost twice the number of TCP units as one attack unit of Model 1, which represents an increase in attack potency of nearly 200 percent. The present study provides an expanded basis to explore FB-Shrew attack patterns that may be utilized by attackers. Moreover, the damage that could be inflicted by such attack and the extent to which defense strategies are capable of mitigating the attack's impact could be assessed more precisely by defenders.
PACAP and PAC1 receptor expression in pancreatic ductal carcinoma

Pancreatic carcinoma is one of the most malignant diseases and is associated with a poor survival rate. Pituitary adenylate cyclase activating polypeptide (PACAP) is a neuropeptide that acts on three different G protein-coupled receptors: the specific PAC1 and the VPAC1/2 that also bind vasoactive intestinal peptide. PACAP is widely distributed in the body and has diverse physiological effects. Among other things, it acts as a trophic factor and influences proliferation and differentiation of several different cells both under normal circumstances and tumourous transformation. Changes of PACAP and its receptors have been shown in various tumour types. However, it is not known whether PACAP and its specific receptor are altered in pancreatic cancer. Perioperative data of patients with pancreas carcinoma was investigated over a five-year period. Histological results showed Grade 2 or Grade 3 adenocarcinoma in most cases. PACAP and PAC1 receptor expression were investigated by immunohistochemistry. Staining intensity of PAC1 receptor was strong in normal tissues both in the exocrine and endocrine parts of the pancreas, the receptor staining was markedly weaker in the adenocarcinoma. PACAP immunostaining was weak in the exocrine part and very strong in the islets and nerve elements in non-tumourous tissues. The PACAP immunostaining almost disappeared in the adenocarcinoma samples. Based on these findings a decrease or lack of the PAC1 receptor/PACAP signalling might have an influence on tumour growth and/or differentiation.
Big Data Assisted CRAN Enabled 5G SON Architecture

The recent development of Big Data, Internet of Things (IoT) and 5G network technology offers a plethora of opportunities to the IT industry and mobile network operators. 5G cellular technology promises to offer connectivity to massive numbers of IoT devices while meeting low-latency data transmission requirements. A deficiency of the current 4G networks is that the data from IoT devices and mobile nodes are merely passed on to the cloud and the communication infrastructure does not play a part in data analysis. Instead of only passing data on to the cloud, the system could also contribute to data analysis and decision-making. In this work, a Big Data driven self-optimized 5G network design is proposed using the knowledge of emerging technologies CRAN, NVF and SDN. Also, some technical impediments in 5G network optimization are discussed. A case study is presented to demonstrate the assistance of Big Data in solving the resource allocation problem.
Design and Verification of Analog Integrated Circuits Using Free or Open source EDA Tools

In this paper, a design methodology for carrying out all the steps involved in a typical analog design flow, using free or open source electronic design automation [EDA] tools is proposed. Implementation of a three stage CMOS operational amplifier is chosen for demonstration. gEDA-gschem tool is utilized for schematic capture and SPICE net list generation. Electric-VLSI is a state of the art EDA tool which is used for laying out the op-amp, design rule checking [DRC], verifying layout versus schematic [LVS] and generating parasitic extracted SPICE net list. The SPICE net list are simulated with the help of versatile, electronics and electric circuit simulator, Ngspice. The scripting language provided by Ngspice is used for performing corner analysis and Monte-Carlo simulations. Simulation results reveal that the designed operational amplifier meets the desired specifications. Corner and Monte-Carlo analysis show that the op-amp is robust against process variations and mismatch.
Body weight and healthy diet among elderly Turkish immigrants

Summary In the Sag ˘lik study, 100 elderly men and women in Germany with a Turkish mi- grant background were questioned about body weight/body size, their fruit, veg- etable and meat consumption and their income, among other things. The results reveal, particularly among women, a lower income and an exceptionally high prevalence of overweight and obesity. There was a significant correlation between lower income and greater body weight. Both men and women consume signifi- cantly low amounts of fruit and vegetables, in comparison with recommendations, whereby this consumption increases with higher incomes. There is a clear need for nutritional health promotion measures for the target groups, which to begin with appear more urgent for women than for men.
Learning-based model reduction and control of underactuated balance robots

OF THE DISSERTATION Learning-based Model Reduction and Control of Underactuated Balance Robots By KUO CHEN Dissertation Director: Jingang Yi Underactuated robots are mechanical systems with fewer con t ol i puts than their degrees of freedom (DOF). Inverted pendulums, bicycles and wa lking robots are a few examples of such systems. Underactuated balance robots are underactuated robots that must perform the balancing and tracking tasks simultaneous ly. The balancing task requires the robot to maintain its balance around possibly uns table equilibrium points, while the tracking task requires it to track desired traject ories. For these competing tasks, a common guideline to design controllers is to identi fy a low dimensional subspace of the state space, called a latent manifold, on which t e balancing and tracking tasks are consistent and compatible. The approach of latent ma ifold identification is called model reduction. Previous works apply model reducti on to physical-principled models with well understood dynamics structures. This diss ertation proposes machine
Evaluation of the efficiency of the Somaticell® diagnosis of an indirect somatic cell-count in buffalo milk.

Two experiments were conducted with a view to evaluating the Somaticell® diagnosis involving an indirect somatic cell-count in buffalo milk. In experiment A, six Murrah buffaloes in different lactation phases were subjected to Somaticell®, CMT and Alizarol tests. In experiment B, 49 Murrah buffaloes in different lactation phases were used, giving a total of 196 samples, on which Somaticell® and CCS tests were carried out using an electronic counter. It was observed that the counting of somatic cells performed using Somaticell® provided values significantly higher than those obtained when using an electronic counter. The values obtained using the Somaticell® test were 4.7 times higher than those obtained for the same samples by way of electronic counting of somatic cells. Comparison of Somaticell® and CCS electronic counting for each mammary gland separately revealed a disparity between the mean values obtained using both techniques, with the lowest values obtained using Somaticell® 69 times higher than those obtained using CCS. The correlations between both tests were low and insignificant, demonstrating that the techniques behave differently when counting the somatic cells in buffalo milk. Viana et al. / Rev. Ci. Agra. , v.53, n.1, p.24-30, Jan/Jun 2010
Sistem Monitoring Untuk Mesin Pelayanan Pelanggan (Studi Kasus Di Etisalat Corporation, Abu Dhabi)

Customer service machines for a telecom operator are tools to prevent customers from churning (switching to another provider). So it is important to know the functional of these machines from time to time. These machines also help telecom operators to reduce the number of branch offices because the machines can indicate the existence of the operator without any branch office. Opening a branch office will cost more than machines because it has to rent a bigger place and more employees and equipments needed. However, sometimes these customer service machines have faults that some or all services cannot function well. For this the telecom operator requires another tool that will monitor the functional of the customer service machines. Another device called a monitoring system is required at all time to 'see' the existence of the machines. The monitoring system unfortunately cannot repair machines. If one machine is known to not function properly, then a technician is required to come and fix the machine. The monitoring system at any given interval polls the machines and requests its status. Afterward it writes the status in the database. Consequently, it is required to build an application interface that reads the database. The technicians can at any time see that status through an application program to find out if any machine requires attention. At the end of the week or at the end of the month technicians’ supervisors can obtain uptime statistics of the machines. Statistics are required as a base of observation and review for future service improvements.
Extra-Auditory Health Effects of Industrial Noise: Survey of Foreign Literature.

Abstract : Based on the literature reviewed in this report there is very substantial evidence that long-term work under industrial sound of 85-95 dBA and above is associated with chronic changes in cardiovascular function, mostly adverse. The best documented change is an impaired regulation of blood pressure, most commonly manifest as an increased prevalance of hypertension in the middle and latter decades of life. There is also evidence for an increased risk of ischemic heart disease. Very conservatively, long-term work under high intensity sound seems associated with an increased risk of cardiovascular disease of at least 60 percent, quite possible with a doubling or more than doubling of risk. Functional neurological changes are common. Other extra-auditory changes are also reported but too few studies of them have been conducted to adequately assess their importance. Interpretation of these observations is subject to the usual constraints inherent in the epidemiological model. (Author)
Report for 2.2.1 Task 3: Develop and Document an Advanced Human System Interface for the Generic Pressurized Water Reactor Simulator

v ACRONYMS . viii 1. PROJECT BACKGROUND . 1 2. THE PROJECT ENVIRONMENT . 1 3. THE BASELINE – THE CURRENT HSSL DISPLAYS . 1 4. DESIGNING AND IMPLEMENTING THE NEW OPERATOR WORK DISPLAYS . 3 5. GENERAL DESIGN PRINCIPLES FOR THE NEW OWDS . 4 5.1 The Design Rationale for the New OWDs . 4 5.2 Display Structure . 5 5.3 Graphical Layout – Visual Clutter and Data-Ink Ratio . 5 5.4 Display Graphics Formats . 7 5.5 Consistent Information Presentation . 8 5.6 Supporting Natural Conventions . 8 5.7 Display Colors – Visual Layering . 9 5.8 Display Colors – Foreground versus Background . 10 5.9 Alarm Graphics – Special Considerations . 10 5.10 Process Interaction . 11 6. RESULT: THE OWDS – EXAMPLES AND EXPLANATIONS . 12 6.1 The Four New OWDS are Selected for Running Scenarios . 12 7. DISCUSSION: SHARED EXPERIENCES THROUGH THE ITERATIVE DESIGN PROCESS. 15 7.1 First Impressions Running the OWDS on the gPWR . 15 8. SHARING EXPERIENCES WITH INL . 18 9. CONCLUSIONS AND FURTHER WORK . 18 10. REFERENCES . 18
The Effect of Alcohol Abuse on Sepsis and the Acute Respiratory Distress Syndrome

Alcohol is the most frequently abused drug throughout the world, and alcohol-related problems are a common occurrence among patients admitted to hospitals and intensive care units. Alcohol affects all tissues of the body, and its effects on immune function and the systemic inflammatory response syndrome remain topics of active investigation. In regard to immune function, alcohol use alters the inflammatory response at several points along the inflammatory cascade. Due to these potent modulating effects on immune function, alcoholic patients have an increased incidence and severity of infection, particularly in the lung. This association between alcohol use and infection is especially evident in the post-operative setting. Once sepsis has developed, patients with a prior history of chronic alcohol abuse are more likely to develop respiratory dysfunction and acute respiratory distress syndrome (ARDS). Chronic alcohol abuse also appears to increase the mortality from ARDS. One possible mechanism by which chronic alcohol abuse may increase susceptibility to acute lung injury is through alterations in pulmonary glutathione homeostasis. This review discusses the epidemiological and experimental evidence for the association between chronic alcohol abuse, sepsis, and the subsequent development of ARDS.
Position Paper of the American Council on Science and Health on Risk Factors for Breast Cancer: Established, Speculated, and Unsupported

Abstract: This article provides the position of the American Council on Science and Health regarding how breast cancer is defined and classified; the magnitude of the public health problem of breast cancer among women; the implications of variation in incidence of breast cancer internationally and with migration; access to health care as a factor in slight differences in incidence and mortality rates among African‐American and white women; and the evidence concerning various proposed human‐breast‐cancer risk factors. The article classifies risk factors as either established, speculated, or unsupported on the basis of available evidence.
Staff Training in Positive Behaviour Support: Impact on Attitudes and Knowledge

Background Positive behavioural support is increasingly viewed as the preferred service approach for people who challenge, but skills are insufficiently widespread. The need for effective staff training has been highlighted as a key factor in high quality service provision, with investigators recommending a multidimensional approach to increase effectiveness and produce changes in work performance. Method Attitudes and knowledge of registered (qualified nurses) and non-registered (unqualified nursing assistants) staff in specialist health care services were assessed via self-completion questionnaires before and after the delivery of a newly accredited taught course in PBS and at a 1-year follow-up. Results Significant increases in knowledge were evident immediately after the training for both groups, with further increases evident over time for the non-registered staff who completed the qualification. Initial changes in attributions immediately after training reverted to baseline levels over time. Enduring change occurred in perceived confidence, which significantly increased both for registered and non-registered staff. Conclusions The training had a positive effect on knowledge and perceived confidence but little enduring effect on attributions or emotional responses. The importance of training conducted in conjunction with allied changes in organizational systems to ensure ongoing management attention is discussed.
Elementos de Gamificação Aplicados no Ensino-Aprendizagem de Programação Web

Gamificação consiste no uso de mecânicas e dinâmicas de jogos para engajar pessoas, resolver problemas e melhorar o aprendizado. Quando aplicada em sala de aula, permite despertar a curiosidade dos alunos e aumentar a sua motivação. Este artigo apresenta um relato de experiência da adoção de elementos de gamificação em uma disciplina optativa do curso de Sistemas de Informação da Universidade Federal do Pará cujo objetivo é ensinar Programação Web. Sendo assim, as atividades da disciplina foram organizadas em fases a fim de que o aluno-jogador pudesse seguir um caminho pré- estabelecido de ensino-aprendizagem. Adicionalmente, definiram-se as pontuações, medalhas e premiação. Esse relato é descrito tanto do ponto de vista do professor-facilitador (ensino) quanto dos alunos-jogadores (aprendizagem).
Mining Big Data: Future Forecast of Weather

Climate gauging is a shot by meteorologists to anticipate the state of the air at some future time and expecting the atmosphere conditions. Climate gauging is the single 'most' imperative pragmatic purpose that meteorology exist as a science. Learning of climate information or atmosphere information in a locale is basic for business, society, agribusiness and vitality; utilized for both residential and business purposes . The estimate can advise a rancher the best time to sow the seeds for germination, it also helps to select the relevant data which has to be send to the airplane and also helps to determine that at what time the airplane has to take off or arrive. It acts lucrative for the occupants of the waterfront districts too, making them mindful of the events of storms. Climate information is considered utilizing information digging method for example 'The Clustering Technique'. By utilizing this procedure, we can locate the shrouded designs in the extensive dataset gathered and after that change the recovered data into the usable data for expectation of the climatic conditions. An assortment of information mining instruments and strategies are accessible in the business, however with a restricted use in the meteorological business.
Combining Locomotion and Grasping Functionalities in Soft Robots

In recent years, the field of soft robotics has grown considerably, demonstrating robots with advanced locomotion capabilities as well as robust grasping and manipulation with respect to their rigid counterparts. The combination of locomotion and grasping capabilities entails a unique set of challenges in soft robotics that have not been fully explored yet, such as the capability to carry a payload without compromising its motion capabilities, and how to adjust changes in the center of mass of the robot. Herein, a soft robotic platform is proposed that demonstrates simultaneous locomotion and grasping. The challenges that such a soft robot would encounter are explored in terms of stability of the robot while supporting a payload and variations in the location of the center of mass. The robot has 13 independently controllable degrees of freedom to study different locomotion and grasping strategies. A passive stiffening methodology is also presented that allows the robot body to statically sustain up to 7.7 times its body weight (BW), and to walk carrying a payload up to 100% times its BW.