Miracle-dz/UniFAR-FTUs huggingface dataset:
TRANSVERSE RESPONSE OF TALL BUILDINGS TAKING INTO ACCOUNT OF THE INTERFERENCE EFFECT

The response of tall buildings to wind depends on many parameters, such as natural wind characteristics, surrounding environment, building size, shape, orientation, and its dynamic properties (mass, damping and stiffness). Also, location of buildings beside each other and their external shape may cause turbulent flows and complex aerodynamic problems that can significantly to the complexity of structural analysis. The analysis will become more complicated if the effect of adjacent buildings accounted in the analysis. An important effect arises when wind flows are interfered by nearly adjacent buildings. Tall buildings are not only affected in the windward direction but also are affected perpendicular to the wind direction. In many cases, the acrosswind response of tall buildings is of major concern in design. In present study, the along wind response of isolated tall rectangular buildings have been obtained for different reduced velocity by wind tunnel tests. The height of the interfering buildings was as tall as aeroelastic model. And non-dimensional acrosswind force spectrum was produced with considering neighboring effects for different reduced velocity.
SURVEY ON AUTOMATIC DETECTION OF SENSITIVE ATTRIBUTE IN PRIVACY PRESERVED HADOOP ENVIRONMENT USING DATA MINING TECHNIQUES

: This study has been focused on the automatic detection of sensitive attributes using data mining technique in Hadoop environment. We establish Privacy Preserved Hadoop Environment (PPHE) that automatically detects sensitive attribute using data mining techniques. The proposed PPHE considers Twitter to enable user to post messages. The content of the posted tweets are wide ranging and contains private information such as email addresses, mobile numbers, physical addresses, and date of births. The major purpose of this study is in three folds. At First, we authenticate each twitter user using the combined algorithm RSA and Elgamal Algorithm. In the second, we classify the tweets into private and non-private attributes by using Type-2 Fuzzy Logic System. In the third, we pursue the data suppression technique to compress private tweets.
Q Methodology as a needs assessment tool for biology graduate teaching assistants participating in an instructional training program

The purpose of this study is to demonstrate how Q Methodology can be used as a needs assessment tool for a Biology graduate teaching assistant (GTA) instructional training program. GTAs are used as the instructors of an increasingly diverse population of undergraduate students. GTAs are a diverse population of students with varying amounts of pedagogical preparation, research abilities, and motivation to complete their graduate study. They are often expected to prepare and grade exams, write their own syllabi, design course curriculum, prepare and present lectures, monitor student progress, hold office hours, and assign final grades, all with minimal faculty supervision. Although not all GTAs will become professors, many will, and the teaching assistantship remains the major preparation for their roles as faculty members. Since the majority of science professors have been GTAs, this instructional training program is of critical importance. Approaches to developing instructional training programs for GTAs vary from departmental workshops to campus-wide instructional seminars. Program evaluation is an intrinsic part of assuring that such programs best serve GTA needs, and that GTAs can best fulfill their roles in their respective departments. Q Methodology offers a number of potential advantages over traditional survey techniques for assessing needs of GTAs throughout their graduate school career, allowing program supervisors to evaluate and modify the program relative to GTA needs. Q Methodology allows the researcher to identify and interpret various viewpoints the GTAs hold in regard to graduate school.
A Performance Analysis of Image De-noising Techniques

Image de-noising is a serious challenge in image processing techniques. Noise is broadly categorised as additive and multicative noises. In this paper we will discuss about Gaussian noise, salt and pepper noise, speckle noise and poisson noise. Naturally Images contain some amount of noise. But it’s very difficult to denoise it. So blind deconvolution is used. Therefore simulated noise is added to the image to understand the process of denoising. Because after the addition of above mentioned noises if any other transformation or processing is done to the image then the corresponding noises will also be changed. There we will face difficulties to denoise if you don't know the type of noise. So a known noise is added to the image before processing. now let us come to the de-noising methods, Out of different available method wavelet thresholding method is one of the important approaches for image de-noising. In this paper we propose an adaptive method of image de-noising in the wavelet sub-band domain assuming the images to be contaminated with noise based on threshold estimation for each sub-band. Under this framework the proposed technique estimates the threshold level by applying sub-band of each decomposition level. This paper details the development of wavelet decomposition on the MATLAB platform. The experimental result reveals that transform domain is better than the spatial domain which we can prove and analyze through the quality metrics factors.
The energy and environmental implications of construction in China

Input-output life cycle assessment (LCA) and hybrid LCA models were developed to calculate the energy and environmental impacts of construction projects, rural and urban residential buildings, and an education building in China. Results show that the embodied energy and emissions of construction projects are approximately 30% of national totals. Although operation energy dominates the total life-cycle energy for both urban and rural residential buildings, its share varies significantly (from 75% to 86%) due to the gap in urban and rural living standards and differences in building structure. In the case of the specific building, results of the process-based hybrid model are moderately higher (5% to13%) than the I-O model values and the hybrid model is more specific to the building characteristics.
Effect of Fe2O3 Nanoparticles on Anxiety Behavior and Nociception in Adult Male Rat

Abstract: Background & Aims: Iron is an essential element for correct brain function. Iron deficiency changes some behaviors such as anxiety and nociception. Recently, nano-iron, Ferric or ferro oxide (nano-Fe2O3 or Fe3O4), are used in various applications in agriculture, industry and medicine, but their effects on the heath and behavior is not clear. In this study, the effects of Fe2O3 nanoparticles on animal models of anxiety and nociception were investigated. Methods: Adult male Wistar rats (mean weight: 200-250 g) were used in 12 groups: 3 control groups (receiving saline 0.9%) and 9 groups received nano-Fe2O3 in doses of 0.2, 1 and 5 mg/kg, intraperitoneally. Elevated plus maze apparatus and hot-plate and tail-flick tests were used to evaluate anxiety and nociception, respectively. Data were analyzed by one-way ANOVA and post hock least significant difference (LSD) and P < 0.05 used as significant level. Results: Fe2O3 nanoparticles with dose addition increased open arm time percent (OAT%) (P<0.05). Locomotor activity, just in dose of 5 mg/kg, increased pain delay time in both hot-plate (P<0.01) and tail-flick (P<0.01) tests. Conclusion: Acute administration of Fe2O3 nanoparticle decreases anxiety behaviors in elevated plus maze and increases an acute pain threshold in both hot-plate and tail-flick tests in rats. Keywords: Anxiety, Pain, Fe2O3 nanoparticle, Rat
*Plant Breeding and Acclimatization Institute, Radzików, Poland **Experimental Station of Plant Breeding and Acclimatization, Bartążek, Poland ENDOPHYTE OCCURRENCE IN BREEDING STRAINS OF MEADOW

Breeding strains of cv. ‘Pasja’ (meadow fescue) were examined for Neotyphodium uncinatum occurrence in plants and seeds using immunoblots assays. Differences in endophyte infection of strains were detected. The majority of strains (70%) contained endophytes both in plants and seeds. In some of them (16.7%) endophyte was detected only in plants. Some of tested strains (12.5%) were free from Neotyphodium. Mean level of endophyte infection for basic material of ‘Pasja’ was 46% (ranging from 0 to 90%). The distribution of strains infection may support hypothesis that different share of seeds from breeding strains in basic material of cultivar is the main reason for variable endophyte occurrence in seed lots from different harvest years and different sites.
Practices and Challenges of Using Think-Aloud Protocols in Industry: An International Survey

Think-aloud protocols are one of the classic methods often taught in universities for training UX designers and researchers. Although previous research reported how these protocols were used in industry, the findings were typically based on the practices of a small number of professionals in specific geographic regions or on studies conducted years ago. As UX practices continuously evolve to address new challenges emerging in industry, it is important to understand the challenges faced by current UX practitioners around the world when using think-aloud protocols. Such an understanding is beneficial for UX professionals to reflect on and learn from the UX community’s practices. It is also invaluable for academic researchers and educators to understand the challenges faced by professionals when carrying out the protocols in a wide range of practical contexts and to better explore methods to address these challenges. We conducted an international survey study with UX professionals in various sized companies around the world. We found that think-aloud protocols are widely and almost equally used in controlled lab studies and remote usability testing; concurrent protocols are more popular than retrospective protocols. Most UX practitioners probe participants during test sessions, explicitly request them to verbalize particular types of content, and do not administer practice sessions. The findings also offer insights on practices and challenges in analyzing think-aloud sessions. In sum, UX practitioners often deal with the tension between validity and efficiency in their analysis and demand better fast-paced and reliable analysis methods than merely reviewing observation notes or session recordings.
The dark side of low(er) interest rates

Retirement bene ts in industrialized countries have come under great pressure. How should one conduct monetary policy in this scenario? Do low interest rates necessarily stimulate demand? The paper builds a New Keynesian overlapping generations model. The standard monetary transmission obtains whenever pensions are su ciently generous. Below a critical level of government-provided pensions, however, low interest rates can show their darker side: lower interest rates may turn into the cause of a recession rather than supporting economic activity. This is more likely if households do not want to substitute intertemporally, or if they cannot, for example, because the young are borrowingconstrained and the constraints do not ease su ciently. Using OECD data, we nd some evidence showing that the strength of monetary policy depends on the generosity of the retirement system. Consistent with our model, countries having less generous systems display less responsive monetary policy. ∗Guerrón-Quintana: Boston College, pguerron@gmail.com. Kuester: Bonn University, keith.kuester@unibonn.de. We thank Susanto Basu, Ricardo Reis, seminar participants at Boston College, the Boston Fed, the CBP in Den Haag, the Dutch Central Bank, ETH Zurich, the Federal Reserve Bank of Atlanta, and Hitotsubashi University for comments. We thank Kai Arvai for excellent research assistance.
Comparative Analysis of Feature Matching Algorithms In Region Duplication Detection

: Images works as a source of information which can be used as an evidence for any cyber-crime investigation. Because of technological growth, the availability of image morphing software’s the true information in images can be modified. Modifying the content from any digital image is called tampering or forgery. Detecting the forgery done on any image is very crucial. Region duplication is one of the kind of digital image forgeries where particular portion is copied and pasted on same image at different location. Many duplication detection methods have been delivered good result. In this work comparative analysis of different block based feature matching algorithms are explained which are used to detect the duplicated regions present in an image.
Modelling the deposition of fine particulate matter (PM2.5) in the human respiratory tract

In general, particulate matter (PM) or suspended particulate matter (SPM) includes microscopic particles of liquid or solid matter, which are suspended in the atmosphe re. These particles can originate either from natural or from anthropogenic sources (1-4). From a physical point of view, PM can be further subdivided into inhalable coarse particles, including particulate objects with a diameter between 2.5 and 10 μm (PM10), fine particles exhibiting a diameter of 2.5 μm or less (PM2.5), ultrafine particles and soot (5-10). In medical respects, all kinds of airborne particles are classified by the IARC and WHO as Group 1 carcinogens (11), whereby most harmful particulates have the ability to penetrate into deep lung regions, where Original Article
17.1 Advanced Bonding Techniques for Photonic Integrated Circuits

The increase of data volume approximately parallels Moore’s law, thus leading to a bottleneck in today’s networks. While in metro and long haul networks optical communication is well established for many years optics becomes more and more mandatory in short range. To enable optical data transfer for rack to rack or eventually chip to chip applications silicon photonics will be the core technology. Silicon photonics allows combining the benefits of mature Si technology and the superior optical properties of III-V materials. In order to realize such devices, heterogeneous integration of the compound semiconductors on silicon are a key factor. While growth of III-Vs on silicon shows limited success till now, as well as getting the active regions close enough to the silicon waveguides shows to be challenging, wafer bonding overcomes these challenges. Thus, wafer bonding is the preferred solution as it allows integrating defect free structures with highest performance on the SOI platform. Wafer bonding with optical transparent interfaces is the enabling technology to join III-V materials with silicon in order to realize optical data transfer on a single chip even in high volume
Managing Depression as a Long Term Condition

Depression is a ubiquitous term which is used to denote a wide variety of mental conditions. In common language people use the term depression to refer to an experience of undesirable or negative emotions. However, in mental health practice, the term depression is used to refer to a specific syndrome characterized by a cluster of phenomena [1]. It is important to make this distinction as there has been valid concerns about the increase in antidepressant prescribing [2], which may be related to over diagnosis of depression [3]. The syndrome of depression is associated with changes in mood, biological functions, cognitive dysfunctions, and loss of pleasure [1]. All health care practitioners should be aware that such a syndrome and its variants can assume a chronic course. Therefore, strategiesand very importantly-services to manage the condition with a chronic perspective are important.
Employee Innovativeness in Organizational Ecosystems: An Initial Study

Organizational ecosystems are characterised by various structures, relationships, variables and levels. With regard to levels Parsons (1960) enunciates a useful framework with three levels in the hierarchical structure of complex organisations which are technical, organizational and institutional or community levels. The technical level involves an organization‟s performance concerning many activities utilizing knowledge, such as research and development (Parsons, 1960). Within complex organizations technical tasks are undertaken by professionals, experts, skilled and unskilled workers (Kast and Rosenzweig, 1972).
Predictive Estimation of Speech Intelligibility Masked by Noise Interference

A detailed description of the speech intelligibility prediction algorithm using analytical modeling is presented. The efficiency of the proposed algorithm is tested for four types of noise interference: white, pink, brown and typical for classrooms. The consistency of the results with known similar results indicates the correctness of the proposed components of the analytical algorithm. In addition, we compared the results of evaluating speech intelligibility obtained in accordance with the “classical” approach with the results of evaluating the STI index of speech intelligibility, which allowed us to confirm the thesis of a low camouflage ability of white noise at low signal-to-noise ratios.
Neural Networks in Arabic Text processing

In this paper we aim to compare two developed methods to find text parts of long text which were not written by the same author or somebody manipulated with the text. Our work consists of two parts : in the first we developed a combined system of Replicator Neural Networks and ART2 to find outliers in some texts, in the second part we used Convolutional Neural Networks, the method was done by clustering of text parts and then classification of them. The analyzed texts were chosen from benchmark “King Saud University Corpus of Classical Arabic” of Arabic texts as long texts.
An Extensive Study on Power‑Efficient Nature‑Inspired Techniques in Cloud computing Data Centres

Systematic deployment of services within the cloud as well as resources to the cloud consumers via the Internet is known as Cloud computing. The IaaS (Infrastructure as a Service) facility is offered to the cloud user by allowing better access to storage, processing power, networks and basic computational services which comprise both operating systems as well as applications. The resources are made obtainable as Virtual Machines (VMs). Services within the cloud are offered to the cloud consumers on a pay-per-use model on demand and is the utilized services are billed appropriately. The VMs are found to run on several data centers within the cloud, which possess a multitude of resources making use of energy in abundance with the side-effect of alarming carbon emission in the atmosphere. Various research studies have suggested a variant of power-efficient techniques which are intended to minimizing power usage within the data centers. One amongst the popular solutions are algorithms that are inspired by nature. In this research work, a review of those algorithms inspired by nature for the ideal power utilization within the data centers of the cloud is exercised. Proper management of energy usage in the data centers and the Power-Efficient Nature inspired techniques for the data centers within the cloud are explored and a comparative evaluation of the different power-efficient methods is executed. This research work empowers both academic researchers as well as industry personnel in the data centers of the cloud to understand the literature development for ideal power-efficient methods for the data centers in the Cloud.
Detection of Acute Lymphocytic Leukemia using Statistical Features

Accurate diagnosis of Leukemia is an important issue in the medical field in order to provide effective treatment to the patient. Leukemia is caused due to the abnormalities in the lymphatic (immune) system in our body. The chance of getting affected by leukemia is more common in children than adults. Cell types that involved in leukemia are white blood cells which are potent infection fighters. When leukemia causes abnormal production of WBCs which do not function properly is known as Acute Lymphocytic Leukemia (ALL) whereas, in other type of leukemia called Chronic Lymphocytic Leukemia (CLL), immature WBCs are capable of performing their functions normally. When compared to Chronic Leukemias, Acute Leukemias are more hazardous. In this paper Acute Lymphocytic Leukemia (ALL) is focused. In this work, from the given dataset that consisting of both benign (healthy) & malignant cells, Leukemic cells are detected & classified based on blast cells’ morphology. There are various image processing techniques to detect leukemia and its types. Linear, SVM and classifiers are analyzed. SVM-R produced accuracy, sensitivity and specificity of 86.67%, 85%, and 90% respectively for noisy data.
Spam Filter Using Machine Learning Techniques

: Email spam or garbage email (undesirable email "more often than not of a business nature conveyed in mass") is one of the real issues of the today's Internet, conveying money related harm to organizations and irritating individual clients. Among the methodologies created to stop spam, separating is an essential and well known one. Regular uses for mail channels incorporate sorting out approaching email and evacuation of spam and PC infections. A less regular utilize is to assess active email at a few organizations to guarantee that workers follow fitting laws. Clients may likewise utilize a mail channel to organize messages, and to sort them into envelopes in view of topic or other criteria. Mail channels can be introduced by the client, either as isolated projects, or as a component of their email program (email customer). In email programs, clients can make individual, "manual" channels that at that point naturally channel mail as indicated by the picked criteria. In this paper, we introduce an overview of the execution of five regularly utilized machine learning strategies in spam separating. Most email projects now additionally have a programmed spam separating capacity.
Urban planning of sewer infrastructure: Impact of population density and land topography on environmental performances of wastewater treatment systems

Urban expansion is a multifaceted concept which has several direct or indirect environmental effects. This work intends to use Life Cycle Assessment (LCA), to assess the effect of urban expansion on sewer infrastructure for small and medium communities (1000-5000 inhabitants). This effect is discussed in relation to land topography and population density in terms of urban planning issues. The LCA results confirm the huge contribution of the sewer on the entire footprint of the sanitation system. They highlight the environmental effect of urban sprawl on the sewer itself for all impact categories except eutrophication which is mainly linked to the efficiency of the wastewater treatment plant (WWTP). It finally advocates for scientific research perspectives and associated assessment tools to compare centralized sewerage systems to clusters of wastewater treatment units especially on uneven land and/or existing sprawled suburbs.