Miracle-dz/UniFAR-FTUs huggingface dataset:
A Longitudinal Investigation of Personal Computers in Homes: Adoption Determinants and Emerging Challenges

While technology adoption in the workplace has been studied extensively, drivers of adoption in homes have been largely overlooked. This paper presents the results of a nation-wide, two-wave, longitudinal investigation of the factors driving personal computer (PC) adoption in American homes. The findings revealed that the decisions driving adoption and non-adoption were significantly different. Adopters were driven by utilitarian outcomes, hedonic outcomes (i.e., fun), and social outcomes (i.e., status) from adoption. Non-adopters, on the other hand, were influenced primarily by rapid changes in technology and the consequent fear of obsolescence. A second wave of data collection conducted six months after the initial survey indicated an asymmetrical relationship between intent and behavior, with those who did not intend to adopt a PC following more closely with their intent than those who intended to adopt one. We present important implications for research on adoption of technologies in homes and the workplace, and also discuss challenges facing the PC industry.
Self-con…rming in ‡ation Persistence

In this paper we simulate a central bank subject to the misperception that prices are indexed to past in ‡ation in periods when …rms are unable to re-optimise. It thinks, in other words, that in ‡ation is intrinsically persistent. The central bank sets monetary policy optimally subject to this belief. The central bank updates its beliefs about indexation using a constant gain learning scheme. The data generated by such policy lead to beliefs about in ‡ation persistence being e¤ectively self-con…rming in a wide variety of setttings. Most importantly, ‡exible prices generate a steep Phillips curve under which the central bank's policy actions have a powerful e¤ect on the process for in ‡ation. These results o¤er a tentative answer to why it appears that in ‡ation is persistent at some times and in some countries, and at others not. The answer is that changes in the degree of price stickiness and policy-makers'priors about in ‡ation indexation can lead to large changes in reduced form in ‡ation persistence. This paper is preliminary and incomplete – please do not quote without the authors' permission. We thank, without prejudicing, for helpful conversations, views expressed in this paper are those of the authors and not necessarily those of the Bank of England nor the Bank's Monetary Policy Committee.
Position-based navigation using multiple homographies

In this paper we address the problem of visual navigation of a mobile robot which simultaneously obtains metric localization and scene reconstruction using homographies. Initially, the robot is guided by a human and some scenes during the trip are stored from known reference locations. The interest of this paper consist in the possibility of getting real and precise data of the robot motion and the scene, which presents some advantages over other existing approaches. For example, it allows the robot to carry out other trajectories than the executed during the teaching phase. We show an extensive analysis of the output in presence of errors in some of the inputs.
Vision-Based Human Motion Analysis for Event Recognition

Event detection and recognition is an active and challenging topic recent in computer vision. The technique could be applied in many visual surveillance systems. This paper describes a new method of recognizing events from video sequences in an office environment. The proposed approach is the vision based human motion analysis via motion history image (MHI) sequences and is invariant to body shape, clothing and position. Combined with edge detection, geometrical characteristics of the human shape in the MHI sequences are considered as the features. An advantage of the proposed method is that the event detection framework is easy to extend by inserting the descriptions of events.
Evaluation of wavelet based linear subspace techniques for face recognition

Face recognition is a complex visual classification task which plays an important role in computer vision, image processing and pattern recognition. Research concerning the face recognition started nearly in 1960s. The initial research directions in 1960’s are based on locating the features such as eyes, ears, nose and mouth on the photograph and calculating the distance between the reference image and the stored images. In 1990’s, researchers introduced linear subspace techniques, statistics related techniques, to face recognition problems. The introduction of the linear subspace techniques is a milestone in the face recognition concept. The main objective of the thesis is to improve the recognition rate of existing face recognition methods for large databases with varying pose, expression and environmental conditions (lighting, rainy etc). The human skill of identifying thousands of people even after so many years with different aging, different light conditions and viewing conditions excited many researchers to focus in face recognition systems. Researchers have developed various biometric techniques to identify or recognize persons with their physical characteristics like finger, voice, face etc. These biometric techniques have their own advantages and drawbacks as well. Among all the biometric techniques face recognition has a distinct advantage of collecting the required data or image without individual cooperation. In this work, we are attempting to answer the following research questions: • Is the face recognition system invariant to face expressions? • Is the face recognition system invariant to environmental conditions (like background, climate changes)? • Is the face recognition system invariant to viewing conditions? • Is the face recognition system giving higher performance or high recognition rate for large databases? • Is the wavelet based linear subspace technique a good alternative to perform face recognition tasks? • What is the efficiency of the wavelet based linear subspace technique when compared with its counter parts? In this thesis, different linear subspace techniques like principal component analysis (PCA), independent component analysis (ICA) and linear discriminant analysis (LDA)
Constraint-Based Mining of Sets of Cliques Sharing Vertex Properties

We consider data mining methods on large graphs where a set of labels is associated to each vertex. A typical example concerns the social network of collaborating researchers where additional information concern the main publication targets (preferred conferences or journals) for each author. We investigate the extraction of sets of dense subgraphs such that the vertices in all subgraphs of a set share a large enough set of labels. As a first step, we consider here the special case of dense subgraphs that are cliques. We proposed a method to compute all maximal homogeneous clique sets that satisfy user-defined constraints on the number of separated cliques, on the size of the cliques, and on the number of labels shared by all the vertices. The empirical validation illustrates the scalability of our approach and it provides experimental feedback on two real datasets, more precisely an annotated social network derived from the DBLP database and an enriched biological network concerning protein-protein interactions. In both cases, we discuss the relevancy of extracted patterns thanks to available domain knowledge.
Hereditary renal amyloidosis caused by a heterozygous G654A gelsolin mutation: a report of two cases

Finnish-type familial amyloidosis (FAF) is a rare hereditary systemic amyloidosis that mainly exhibits cranial neuropathy. We describe a Japanese family with FAF manifested predominantly as renal amyloidosis. The proband was a 42-year-old woman with a 21-year history of proteinuria due to renal amyloidosis. Her mother was subsequently diagnosed with a similar disorder. After the first renal biopsy, both patients were followed up routinely for a period of 14 years. Genetic analysis of DNA samples revealed a heterozygous G654A gelsolin mutation. Severe renal involvement has not been reported previously in patients with FAF bearing a heterozygous gelsolin mutation.
Negotiating the Cultural Steps in Developing an Online Intervention for Korean American Intimate Partner Violence

ABSTRACT Korean American (KA) immigrants experiencing intimate partner violence (IPV) underutilize existing services, but instead rely on KA clergy for assistance. However, there had not yet been an intervention curriculum developed for KA clergy to help them address IPV in their congregations. There was a lack of understanding regarding what needed to be included in an intervention curriculum for KA clergy, as well as the most effective form of curriculum design and delivery for such an intervention. This article discusses the process of developing an online IPV intervention curriculum for KA clergy to increase their capacity for IPV prevention and intervention within their congregations. Researchers developed Korean Clergy for Healthy Families by incorporating feedback from expert consultants and engaging study participants. The result is an IPV curriculum that speaks to participants’ cultural values and religious beliefs, and identifies barriers KA clergy experience when confronted with IPV. Specific steps to assist those who would want to develop culturally appropriate interventions are provided.
Explicit Occlusion Modeling for 3D Object Class Representations

Despite the success of current state-of-the-art object class detectors, severe occlusion remains a major challenge. This is particularly true for more geometrically expressive 3D object class representations. While these representations have attracted renewed interest for precise object pose estimation, the focus has mostly been on rather clean datasets, where occlusion is not an issue. In this paper, we tackle the challenge of modeling occlusion in the context of a 3D geometric object class model that is capable of fine-grained, part-level 3D object reconstruction. Following the intuition that 3D modeling should facilitate occlusion reasoning, we design an explicit representation of likely geometric occlusion patterns. Robustness is achieved by pooling image evidence from of a set of fixed part detectors as well as a non-parametric representation of part configurations in the spirit of pose lets. We confirm the potential of our method on cars in a newly collected data set of inner-city street scenes with varying levels of occlusion, and demonstrate superior performance in occlusion estimation and part localization, compared to baselines that are unaware of occlusions.
Improving Pointing in Graphical User Interfaces for People with Motor Impairments Through Ability-Based Design

Pointing to targets in graphical user interfaces remains a frequent and fundamental necessity in modern computing systems. Yet for millions of people with motor impairments, children, and older users, pointing—whether with a mouse cursor, a stylus, or a finger on a touch screen—remains a major access barrier because of the fine-motor skills required. In a series of projects inspired by and contributing to ability-based design, we have reconsidered the nature and assumptions behind pointing, resulting in changes to how mouse cursors work, the types of targets used, the way interfaces are designed and laid out, and even how input devices are used. The results from these explorations show that people with motor difficulties can acquire targets in graphical user interfaces when interfaces are designed to better match the abilities of their users. Ability-based design, as both a design philosophy and a design approach, provides a route to realizing a future in which people can utilize whatever abilities they have to express themselves not only to machines, but to the world.
Awareness and Decision Making on Health Seeking and Utilization Behaviors Among Substance Abuse Youths

Substance abuse has continued to increase in Tanzania particularly among youth with minority of them seeking the available health services. This study sought to determine the relationship between awareness and decision making on health seeking and utilization behaviors among youth involved in substance abuse in Kinondoni municipality, Dar es Salaam. Concurrent mixed methodology was used. Data were collected among youth with substance abuse problems through face-to-face interviews (n=300) using a structured survey questionnaire. In addition, in-depth interviews (n=23), and focus group discussions (n=5) were conducted. The quantitative data were analyzed using SPSS version 23. Content analysis was used for analyzing qualitative data. Results showed that (74.3%, n=223) of the respondents did not seek and utilize the available treatment options. The majority (62.4%, n=187) of them did not know that their substance abuse problems can be treated using the available treatment options, and 78.2% (n=235) of the participants had little or no concerns about their substance abuse problems. The majority of participants had little information regarding the treatment of substance abuse and major sources of information about substance abuse treatment options were through friends and families followed by radio and television. The reasons related to not seeking and utilizing the available health services may be associated with the low awareness levels of the available treatment options among individuals with substance abuse, little belief that their substance abuse problem can be treated, and having less or no concern about their substance abuse problem. Thus future studies are needed to examine the accessibility and acceptability of the available rehabilitation services for substance abuse in Dar es Salaam.
Flexibility or Constraint? The Implications of Mothers’ and Fathers’ Nonstandard Schedules for Children’s Behavioral Outcomes

Approximately 17.7% of the U.S. workforce is employed in a nonstandard schedule. Research thus far indicates that these schedules negatively influence children’s behavioral development. However, few studies examine the roles of the child’s gender and age. To broaden understanding of the relationships between nonstandard schedules and child behavior, and how these relationships may depend on the gender and age of the child, I analyze data from the National Longitudinal Survey of Youth-1979 and its Child Supplement from 1992 to 2006. My findings show that some types of parental nonstandard shifts, such as evening and night shifts, are associated with fewer behavioral problems among children, though these results depend on the gender and age of the child. In contrast, parents’ rotating and split shifts are associated with more behavior problems among children, indicating that it is relatively unstable and unpredictable work schedules that may have the most harmful associations with children’s outcomes.
Rail and turnout detection using gradient information and template matching

This paper presents a railway track and turnout detection algorithm which is not based on an empirical threshold. The railway track extraction is based on an edge detection using the width of the rolling pads. This edge detection scheme is then used as an input to the RANSAC algorithm to determine the model of the rails. The turnout detection scheme is based on the Histogram of Oriented Gradient (HOG) and Template Matching (TM). The results show (i) reliable performance for our railway track extraction scheme and (ii) a correction rate of 97.31 percent for the turnout detection scheme using a Support Vector Machine (SVM) classifier.
Bone marrow derived cell-seeded extracellular matrix: A novel biomaterial in the field of wound management

Aim: Extensive or irreversible damage to the skin often requires additional skin substitutes for reconstruction. Biomaterials have become critical components in the development of effective new medical therapies for wound care. Materials and Methods: In the present study, a cell matrix construct (bone marrow-derived cells (BMdc) seeded extracellular matrix [ECM]) was used as a biological substitute for the repair of full-thickness skin wound. ECM was developed by decellularizing fish swim bladder (FSB). Goat bone marrow-derived cells (G-BMdc) were seeded over this decellularized matrix. Efficacy of this cell matrix construct in wound repair was tested by implanting it over 20 mm2 × 20 mm2 size fullthickness skin wound created over the dorsum of rat. The study was conducted in 16 clinically healthy adult rats of either sex. The animals were randomly divided into 2 equal groups of 8 animals each. In Group I, animal’s wounds were repaired with a cellular FSB matrix. In Group II, wounds were repaired with G-BMdc seeded a cellular FSB matrix. Immune response and efficacy of healing were analyzed. Results: Quality of healing and immuno tolerance to the biological substitute was significantly better in Group II than Group I. Conclusion: Seeding with BMdc increases the wound healing potency and modulates the immune response to a significantly negligible level. The BMdc seeded acellular FSB matrix was found to be a novel biomaterial for wound management.
Investigating Iraqi EFL College Students' Attitude towards Using Cooperative Learning Approach in Developing Reading Comprehension Skill

This study aims at investigating Iraqi EFL college learners’ attitudes toward using cooperative Learning approach on developing reading comprehension skill. The study is restricted to third– year college students of the English language in Misan Governorate during the second term of the academic year 2015–2016. The number of the whole population is (200) which is distributed into two types: pilot and main. The sample of the study consists of 40 students. To achieve the aim of the study, students' questionnaire consisting of (46) items is applied as an instrument. In order to get required data, a t-test analysis shows a statistically significant difference about learners’ attitudes toward using cooperative learning approach on developing reading comprehension skill. The obtained results are that: which refer to (Cooperative learning helps everyone reach the goal equally) from cooperative learning and (Reading in English is difficult for me) form Reading comprehension. Gain the low effectiveness. They got a weighted mean 56% and 40%. Items number (11, 29, 37, 43) which refer to (Cooperative learning requires much more time to study) & (I think reading the texts is easier if I study within a group) from cooperative learning and (I forward to coming to my reading class.)& (I m a afraid of making mistakes in my reading class) form Reading comprehension. All got (96%).
A spatial adaptive filter for smoothing of non-Gaussian texture noise

This paper contributes a novel technique for reducing the interference of non-Gaussian texture noise from images. Since the inherent properties of texture noise are very different from those of Gaussian white noise, the basic assumption of conventional image denoising techniques is invalid. Here we present a spatial adaptive filtering scheme to remove non-Gaussian texture noise from textile images based on local and non-local similarities. In order to exploit the high correlations among pixels, pixels with uniform texture local regions are estimated differently from those pixels located near edges, that is, for points located in local uniform texture regions, Gaussian weighted averaging of their neighbors can achieve the adaptive effect of the human visual system, whereas for edge points, to find pixels with similar local statistics both in the vicinity and far away can produce a sufficient set of pixels for reasonable averaging. This filtering strategy is applied to textile images corrupted by texture noise and the performance is demonstrated to outperform current state-of-art image denoising techniques. non-Gaussian
An Analysis of Accuracy and Learning in Software Project Estimating

This paper presents a study into the accuracy of different dimensions of IT project estimating: schedule, budget & effort. The study is based on a dataset of 171 projects that have been collected at the IT-department of a large Dutch multinational company. The paper also analyses whether there is any learning (improvement) effect over time. Our results show that there is no relation between accuracy of budget, schedule and effort in the analyzed organization. Besides, they show that over time there is no change of the accuracy effectiveness and efficiency. The paper reflects and provides recommendations on how to improve the learning from historical estimates.
Design an empathic virtual human to encourage and persuade learners in e-learning systems

Studies indicate that making learners feel good is important only minor to clear knowledge transformation. Many studies have tried to use virtual humans as a part of interface in learning systems to increase the effect of instructions. Based on social interaction and pedagogical theories, many e-learning systems use animated films or virtual reality to boost human-computer engagement and ease their negative emotions. However, affective learning systems still need much research to improve their functionalities and usability. This study proposed a convenient approach to develop an emotionally interactive learning system; learners can express their emotions by mouse-clicking while learning. A virtual human was created to empathically react to learners in proactive and reactive ways to encourage and persuade them into persistent learning and help achieve their goals. Experimental results show that, averagely, subjects can tell virtual human's emotions and agree to its empathic reactions. Persuasion conducted by virtual human could not increase subjects' learning time, but could significantly increase their completion rate of exercises.
Religious Orientation and Health Status: Predictors of Adult Attachment Behaviors?

A self-report scale used to measure Intrinsic/Extrinsic religiosity in adults and children. It consists of 20 items (11 extrinsic, 9 intrinsic). Items include such statements as “I pray mainly to gain relief and protection” (item 8; extrinsic) (3). A revised form of the Age Universal I/E was used for this study and consisted of 14 items.
Twitter population sample bias and its impact on predictive outcomes: A case study on elections

In the past years a lot of effort has been spent analyzing online social network data to understand how the world reality is reflected in the "virtual" world. Twitter is by far the network most used in these studies, given its policy of public data availability. However, a big discussion is still on on whether the data available is enough to make user characterization or event outcomes prediction, and what are the pitfalls people do not usually account for. In this direction, we propose a new methodology for drawing representative samples from Twitter data, which is divided into four phases: (i) user filtering, (ii) user demographic characterization, (iii) user sampling, and (iv) event prediction. The methodology is tested into a common scenario in Twitter event outcome prediction: elections. The methodology was tested with municipality elections from six different Brazilian cities, and compared to official election results. Results show it is worth further investigating the topic, but that a very hight number of messages is required to match real data distributions.