Miracle-dz/UniFAR-FTUs huggingface dataset:
"Joy for what it is": Narratives of two mothers on raising their children with disabilities

The purpose of this study was to explore the experiences of two mothers of children with disabilities on parenting their children and navigating the world of disabilities. For many parents, the diagnosis of a child with disabilities represents a form of interpersonal loss through the loss of the imagined child. Mothers are often identified as the primary caregivers of their children with disabilities and are often at the front-end of seeking, providing, and advocating for medical, education, and social services. Employing qualitative research methods, autoethnography and narrative inquiry were used to reveal the mothers’ experiences. Through conversational interviews and journaling, data was collected for the scope of the study. The findings reaffirmed the educational and social challenges that stem out of parenting a child with disabilities. The mothers however, did not cease to address the myriads of joy and growth that they experienced as a result of parenting their children. The mothers discussed the different roles that they have assumed throughout their journeys indicating that their parental role always took precedence over all other roles. The results of this study offer a number of implications for educators, service providers, and fellow parents. Of these implications, the need for educators and service providers to envision possibility and capability rather than be restrained by medical diagnosis and labels. Educators and service providers must view the child as a whole while valuing input from the parents on the children’s needs and capabilities. Open, honest, and ongoing communication and collaboration among the educators, service providers, and parents is key in providing children with disabilities the services that best meet their needs. This study also highlighted the need for parents of children with disabilities to see for their own physical and mental health for it is critical in maintaining their strength to resume their parenting journey. Finally, parents of children with disabilities are encouraged to seek support from support groups and networks that may provide them with assistance and help get rid of feelings of alienation in the unknown world of disabilities. “JOY FOR WHAT IS”: NARRATIVES OF TWO MOTHERS ON RAISING THEIR CHILDREN WITH DISABILITIES A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Education Approved: ________________________________ Dr. Amy J. Petersen, Committee Chair ________________________________ Dr. Rodney Dieser, Committee Member ________________________________ Dr. Benjamin Forsyth, Committee Member ________________________________ Dr. Christopher Kliewer, Committee Member Zeina H. Yousof University of Northern Iowa December 2016
Hierarchical Temporal Memory Concepts , Theory , and Terminology

HTMs are unlike traditional programmable computers. With traditional computers, a programmer creates specific programs to solve specific problems. For example, one program may be used to recognize speech and another completely different program may be used to model weather. HTM, on the other hand, is best thought of as a memory system. HTMs are not programmed and do not execute different algorithms for different problems. Instead, HTMs “learn” how to solve problems. HTMs are trained by exposing them to sensory data and the capability of the HTM is determined largely by what it has been exposed to.
Forming A Random Field via Stochastic Cliques: From Random Graphs to Fully Connected Random Fields

Random fields have remained a topic of great interest over past decades for the purpose of structured inference, especially for problems such as image segmentation. The local nodal interactions commonly used in such models often suffer the short-boundary bias problem, which are tackled primarily through the incorporation of long-range nodal interactions. However, the issue of computational tractability becomes a significant issue when incorporating such long-range nodal interactions, particularly when a large number of long-range nodal interactions (e.g., fully-connected random fields) are modeled. In this work, we introduce a generalized random field framework based around the concept of stochastic cliques, which addresses the issue of computational tractability when using fully-connected random fields by stochastically forming a sparse representation of the random field. The proposed framework allows for efficient structured inference using fully-connected random fields without any restrictions on the potential functions that can be utilized. Several realizations of the proposed framework using graph cuts are presented and evaluated, and experimental results demonstrate that the proposed framework can provide competitive performance for the purpose of image segmentation when compared to existing fully-connected and principled deep random field frameworks.
The European Commission Stepping up Both the Efficiency and Equity of Education and Training Systems

This article analyses the Communication of the European Commission (EC) devoted to efficiency and equity of European education systems. It shows the Commission's difficulties in integrating the multiple dimensions of education equity and the confusion between pedagogical and economical notions of efficiency. The authors also analyse the means proposed by the Commission to foster equity and efficiency at different education levels. Under the guise of a specific interest in pre-schooling, the arguments concerning compulsory education were rather lightweight and incomplete, and those on higher education worrying. This article raises the concerns and questions that remain after the reading of this Communication.
CORRELATION MAXIMIZATION IN REGRESSION MODELS BASED ON CONVEX COMBINATIONS

A new regression method based on convex correcting procedures over sets of predictors is developed. In contrast to previously developed approach based on minimization of generalized error, the proposed one utilies correcting procedures of maximal correlation with the target value. In the proposed approach a concept of a set of predictors irreducible against target functional is used where irreducibility is understood as lack of combinations of at least the same value of the functional after removing any of its predictors. Sets of combinations simultaniously irreducilbe and unexpandable are used during the construction of a prognostic rule. Results of some computational experiments described in the present article show an efficiency comparison between the two approaches.
Sensor Network Optimization Using a Genetic Algorithm

In this paper, we propose an efficient method based on genetic algorithms (GAs) to solve a sensor network optimization problem. Long communication distances between sensors and a sink (or destination) in a sensor network can greatly drain the energy of sensors and reduce the lifetime of a network. By clustering a sensor network into a number of independent clusters using a GA, we can greatly minimize the total communication distance, thus prolonging the network lifetime. Simulation results show that our algorithm can quickly find a good solution. This approach is also applicable to multiple network topologies (uniform or non-uniform) or shortest distance optimization problems . Keyword: Genetic algorithm, clustering, network optimization, shortest distance.
Net-mobile embodied agents

The Talking Heads experiment currently being conducted at Sony CSL Paris implements a network of mobile cognitive agents. Each node of the network consists of a workstation with two digital cameras through which the agents can perceive the world. When installed on a node, agents construct classifications of what they ’see’ through the cameras and interact with each other to develop a simple language for communicating their representations to each other. Travel between the nodes takes place over the Internet, using standard communications protocols.
A multiple-feature framework for modelling and predicting transcription factor binding sites

MOTIVATION The identification of transcription factor binding sites in promoter sequences is an important problem, since it reveals information about the transcriptional regulation of genes. For analysing transcriptional regulation, computational approaches for predicting putative binding sites are applied. Commonly used stochastic models for binding sites are position-specific score matrices, which show weak predictive power. RESULTS We have developed a probabilistic modelling approach, which allows to consider diverse characteristic binding site properties to obtain more accurate representations of binding sites. These properties are modelled as random variables in Bayesian networks, which are capable of dealing with dependencies among binding site properties. Cross-validation on several datasets shows improvements in the false positive error rate and the significance (P-value) of true binding sites.
Keefektifan Pembelajaran Tipe TPS dan JIGSAW Ditinjau dari Prestasi Belajar Matematika dan Karakter Siswa

Tujuan dari penelitian ini untuk: (1) mendeskripsikan keefektifan pembelajaran kooperatif tipe TPS dan tipe Jigsaw ditinjau dari prestasi belajar matematika dan karakter siswa; (2) mendeskripsikan, perbandingan keefektifan pembelajaran kooperatif tipe TPS dengan pembelajaran kooperatif tipe Jigsaw ditinjau dari prestasi belajar matematika dan karakter siswa pada materi bangun ruang sisi lengkung. Penelitian merupakan penelitian eksperimen semu dengan menggunakan dua kelompok eksperimen. Populasi penelitian adalah siswa kelas IX SMP Negeri 1 Banjarnegara yang terdiri atas delapan kelas, sedangkan sampel penelitian terdiri atas dua kelas yang dipilih secara acak. Instrumen penelitian adalah tes prestasi dalam bentuk soal uraian yang terdiri atas pretest dan posttest. Analisis dilakukan dengan uji F dengan Hotelling’s Trace ( = 0,05) untuk mengetahui beda rata-rata kedua kelas secara multivariat. Uji t dengan kriteria Bonferroni ( = 0,05) dilakukan untuk mengetahui variabel terikat mana yang membuat kedua kelas tersebut berbeda. Simpulan dari penelitian ini adalah (1) pembelajaran kooperatif tipe TPS dan tipe Jigsaw efektif ditinjau dari prestasi belajar matematika dan karakter siswa dan (2) pembelajaran kooperatif tipe Jigsaw lebih efektif dibanding pembelajaran kooperatif tipe TPS ditinjau dari prestasi belajar matematika dan karakter siswa pada materi bangun ruang sisi lengkung.Kata kunci: Pembelajaran tipe TPS, Jigsaw, prestasi, karakter siswa. The Effectiveness of Learning TPS and JIGSAW Types Seen from Mathematics Achievement and Student Character AbstractThe purpose of this study was to: (1) describe the effectiveness of TPS and Jigsaw cooperative learning in terms of learning achievement and the student character; (2) describe inequality TPS effectiveness of cooperative learning with Jigsaw cooperative learning in terms of learning achievement and student’s character on the topic content with curved side. The study is quasi-experimental study using two experimental groups. The population of the research includes all students of class IX SMP Negeri 1 Banjarnegara which consists of eight classes, while the sample of the study consisted of two randomly selected classes. The research instrument is the achievement test in the form of essays that consist of the pretest and posttest, and a questionnaire to measure the students character. F test with Hotelling's Trace (α = 0.05) was done to determine the average difference in two classes multivariately. T test with Bonferroni criteria (α = 0.05) was conducted to determine which of the dependent variable that makes these two classes differ. The results showed that: (1) TPS and Jigsaw cooperative learning are effective in terms of learning achievement and the student character; (2) Jigsaw cooperative learning is more effective than TPS cooperative learning in terms of learning achievement and student’s character on the topic content with curved side.Keywords: Learning TPS, Jigsaw types, achievement, student character.
Daring decisions and representative municipal democracy: an exploration within the new river management in the Netherlands

Public sector innovation is often driven by informal groups of visionary key actors (‘transition arenas’). The WaalWeelde project in the Netherlands, where new river management strategies are designed with new groups of stakeholders, is one example. In this article the role of political leadership in these processes of innovation is further explored. In order to mediate between the transition arena, with its long term perspective and experimental character and the conditions of the political domain in which short term results and public support are dominant, it is assumed that a certain element of ‘daring’ within the democratic context is required. In the exploration of daring decision- making, the article focuses on the role of the individual municipal administrator as a mediator between a transition arena and the municipal context in processes of public sector innovation. The most important finding is the importance that the administrators ascribe to individual actors in decision- making processes. Their will to effect change, their skills, resources and strategies are seen as vital in exercising their role as ‘policy entrepreneur’. Linkages with theoretical literature are briefly explored.
Integration of Geological Datasets for Gold Exploration in Nova Scotia

A variety of regional geoscience datasets from Nova Scotia have been co-registered and analyzed using a geographic information system (GIS). The datasets include bedrock and surficial geological maps, airborne geophysical survey data, geochemistry of lake-sediment samples, and mineral occurrence data. A number of line features, including structural lineaments, fold axes and formation contacts, have also been digitized. The GIS uses a quadtree structure, ideally suited to a mixture of polygonal-thematic (e.g., geological maps) and continuous "grey-scale" (e.g., remote sensing, airborne geophysics) raster images. The goal of the study was to create a map showing areas favorable for gold mineralization, based on the distribution of 70 known gold occurrences. Initially, a multi-element geochemical signature was generated using a regression analysis to find the linear combination of geochemical elements that best predict lake catchment bas ins containing a gold occurrence. A predicted gold occurrence map, based on the geochemistry alone, was produced. A method using Bayes' rule was applied to combine other factors important for gold prediction with the geochemical signature. A unique conditions map shows all those areas where a unique set of overlap between the predictor maps occurs. For each unique condition, an a posteriors probability was calculated, resulting in a map depicting probability of gold mineralization. This map confirms that the major known gold districts coincide with areas of high probability. Several new areas of high potential are indicated by the model, although exploration follow-up has not yet been carried out.
A multi-objective method for discovery of pathways in protein-protein interaction networks

Biological pathways such as metabolic or signaling ones play an important role in understanding cell activities and evolution. A cost-effective method to discover such pathways is analyzing accumulated information about protein-protein interactions, which are usually given in forms of undirected networks or graphs. Previous findings show that orienting protein interactions can improve pathway discovery. However, assigning orientation for protein interactions is a combinatorial optimization problem which has been proved to be NP-hard, making it critical to develop efficient algorithms. In the previous report [1], we solved the problem of finding pathways in the protein-protein interaction networks using genetic algorithms. Our proposed algorithm was also compared with the ones of other authors and proved to be better. However, our algorithm gave out only one goal, which was maximizing the weight function of the interactive network, while ignoring the number of standard pathways in the network. Through exper-iments, we have realized that weight functions with high value do not always give the high number of standard pathways. As a result, this report introduces multi-objective generic algorithms to deal with two targets at the same time: Maximizing the weight and function, as well as calculating the number of standard pathways in the interaction network. To extend the previous report, we first studied the mathematical model of the interaction network orientation problem with multi-objective characteristic. Based on such model, we designed a multi-objective genetic algorithm to find the solutions for the problem. Many experimental runs were carried out on the yeasts protein interaction network data set to find the best answer. Results from Multi-Objective Genetic Algorithm (MOGA), when compared with those of our previous proposed GA algorithms (SOGA - Single-Objective Genetic Algorithm), turn out to better solve the problem.
Summaries and the Process of Summarization from Evaluation of Automatic Text Summarization -a Practical Implementation

Text summarization (or rather, automatic text summarization) is the technique where a computer automatically creates an abstract, or summary, of one or more texts. The initial interest in automatic shortening of texts was spawned during the sixties in American research libraries. A large amount of scientific papers and books were to be digitally stored and made searchable. However, the storage capacity was very limited and full papers and books could not be fit into databases those days. Therefore summaries were stored, indexed and made searchable. Sometimes the papers or books already had summaries attached to them, but in cases were no readymade summary was available one had to be created. Thus, the technique has been developed for many years (see Luhn 1958, Edmundson 1969, Salton 1988) and in recent years, with the increased use of the Internet, there have been an awakening interest for summarization techniques. Today the situation is quite the opposite from the situation in the sixties. Today storage is cheap and seemingly limitless. Digitally stored information is available in abundance and in a myriad of forms to an extent as to making it near impossible to manually search, sift and choose which information one should incorporate. This information must instead be filtered and extracted in order to avoiding drowning in it.
Collaborative networking with trust and misbehavior -- a file sharing case

The paper discusses the value of trust in a community network established to share information, skills or resources. We discuss the foundations of trust and show the way to employ it in an open network environment. We also prove by means of simulations, that a system with an element to manage trust and misbehavior can show superior performance to a system without a trust component
Conjugacy of spontaneous blinks in man: eyelid kinematics exhibit bilateral symmetry.

PURPOSE To provide a quantitative description of the conjugacy of human eyelid movements during spontaneous blinks. METHODS Eyelid movements occurring during spontaneous blinks were recorded bilaterally using a modification of the electromagnetic search coil technique. In off-line analyses, covariation of amplitude, peak velocity, and duration of blink down phases were determined for the two eyelids. Interocular differences in the timing of blink onset and offset, and time to peak velocity, also were evaluated. RESULTS Human blink motor control systems act to link tightly the spatial and temporal characteristics of movements of the two eyelids. Data show that human spontaneous blinks are conjugate. Analysis of interocular covariation of blink amplitude, peak velocity, and duration yielded linear functions with high correlation coefficients. Interocular comparison of eyelid movement durations during blinks showed a particularly high correlation. There were negligible interocular differences in blink down-phase onset time, termination time, and time to peak velocity. A small percentage of blinks exhibited interocular differences in amplitude and peak velocity of > 20%; however, even in these cases, blink duration remained tightly linked. CONCLUSION Spatial and temporal properties of eyelid movements occurring during spontaneous blinks are conjugate. These data support the hypothesis that a bilateral gating mechanism regulates blink duration. Elements downstream from the gate may differentially and unilaterally alter blink amplitude and peak velocity, but the duration of blinks remains time-locked for the two eyelids.
SDCCAG8 Interacts with RAB Effector Proteins RABEP2 and ERC1 and Is Required for Hedgehog Signaling

Recessive mutations in the SDCCAG8 gene cause a nephronophthisis-related ciliopathy with Bardet-Biedl syndrome-like features in humans. Our previous characterization of the orthologous Sdccag8gt/gt mouse model recapitulated the retinal-renal disease phenotypes and identified impaired DNA damage response signaling as an underlying disease mechanism in the kidney. However, several other phenotypic and mechanistic features of Sdccag8gt/gt mice remained unexplored. Here we show that Sdccag8gt/gt mice exhibit developmental and structural abnormalities of the skeleton and limbs, suggesting impaired Hedgehog (Hh) signaling. Indeed, cell culture studies demonstrate the requirement of SDCCAG8 for ciliogenesis and Hh signaling. Using an affinity proteomics approach, we demonstrate that SDCCAG8 interacts with proteins of the centriolar satellites (OFD1, AZI1), of the endosomal sorting complex (RABEP2, ERC1), and with non-muscle myosin motor proteins (MYH9, MYH10, MYH14) at the centrosome. Furthermore, we show that RABEP2 localization at the centrosome is regulated by SDCCAG8. siRNA mediated RABEP2 knockdown in hTERT-RPE1 cells leads to defective ciliogenesis, indicating a critical role for RABEP2 in this process. Together, this study identifies several centrosome-associated proteins as novel SDCCAG8 interaction partners, and provides new insights into the function of SDCCAG8 at this structure.
Efficient Service Data Management in Dynamic Environment

With the increasing service-oriented applications, efficient service data management is becoming a practical and important issue. Currently, most exchange messages among different Web services is SOAP, which is represented by XML-formatted data. So, the main task of service data management is to manage XML format message files in order to provide efficient store and query for service requestors. Storing XML documents in relational databases has drawn much attention in recent years because it can leverage existing investments in relational database technologies. However, most former work defines relational schema for XML files based on heuristics without considering application characteristics, hence fails to produce efficient relational schema for various applications. In this paper, we propose an autonomic, workload-aware approach to generate relational schema according to dynamic application characteristics or user specified workload. Our approach adopts the genetic algorithm to find optimal mappings, and an elegant encoding method and related operations are proposed to manipulate mappings using bit strings. We implemented the proposed algorithm and our preliminary experiment results showed that our algorithm was more robust, more suitable for dynamic SOA applications and produced better relational schema than existing work