Testing the RPI data for consistency with the theory of the cost-of-living index

This paper tests the published section level price and weight data used in the compilation of the UK Retail Prices Index for consistency with the theory of the cost-of-living index. We use a nonparametric test of theoretical consistency and bootstrap statistical methods to estimate the probability of consistency

Testing the RPI data for consistency with the theory of the cost-of-living index

This paper tests the published section level price and weight dataused in the compilation of the UK Retail Prices Index for consistencywith the theory of the cost-of-living index. We use a nonparametric testof theoretical consistency and bootstrap statistical methods to estimatethe probability of consistency.

Generalized Inpainting Method for Hyperspectral Image Acquisition

A recently designed hyperspectral imaging device enables multiplexed acquisition of an entire data volume in a single snapshot thanks to monolithically-integrated spectral filters. Such an agile imaging technique comes at the cost of a reduced spatial resolution and the need for a demosaicing procedure on its interleaved data. In this work, we address both issues and propose an approach inspired by recent developments in compressed sensing and analysis sparse models. We formulate our superresolution and demosaicing task as a 3-D generalized inpainting problem. Interestingly, the target spatial resolution can be adjusted for mitigating the compression level of our sensing. The reconstruction procedure uses a fast greedy method called Pseudo-inverse IHT. We also show on simulations that a random arrangement of the spectral filters on the sensor is preferable to regular mosaic layout as it improves the quality of the reconstruction. The efficiency of our technique is demonstrated through numerical experiments on both synthetic and real data as acquired by the snapshot imager.Comment: Keywords: Hyperspectral, inpainting, iterative hard thresholding, sparse models, CMOS, Fabry-P\'ero

The impact of agri-environment schemes on pollination services in England

Agri-environment schemes fund landholders to manage land to achieve environmental objectives and other public goods. Previous research has shown that individual scheme interventions can boost wild pollinator populations locally. However, the effect of an entire scheme at a national scale has never previously been assessed. The location of every intervention implemented in England during 2016 was mapped and schemes’ predicted impact on bee abundance and pollination services was modelled using a validated, processbased spatial model (poll4pop), which simulates foraging and population dynamics. The study considered four wild bee guilds (incorporating bumblebees and solitary bees) and their visitation rates to four pollinator-dependent crops (oilseed rape, field beans, orchard fruit and strawberries). The modelling predicted that the scheme significantly increased ground-nesting (but not tree/cavitynesting) bee populations nationally. There were no significant increases in crop visitation at national scale, but some locally significant increases in ground-nesting bumblebee visitation to oilseed rape and field beans were predicted. Linear regression at 10 km scale was used to determine which interventions were driving increased oilseed rape and field bean visitation and found that hedgerow/woodland edge management dominated, due to high resource quality. Floral margins were estimated to provide more limited benefit, due to later resource phenology and low uptake. Fallow also had a strong effect, despite lower relative resource quality, implying effective placement with respect to crops. Finally, the effect of additional tree-planting interventions (hedgerows, agroforestry, and woodland) on bumblebee abundance and crop visitation (oilseed rape, field beans) was studied. This showed that hedgerow planting would deliver the greatest increase in bumblebee abundance, whereas fruit or willow agroforestry would increase crop visitation the most, due to higher co-location. Based on these findings, recommendations are set out for design of future schemes to help deliver greater and more resilient crop pollination services in arable landscapes

STRATEGI ORANG TUA DALAM MENDAMPINGI ANAK BELAJAR DI RUMAH PADA MASA PANDEMI COVID-19 DI TK SYARIF HIDAYATULLAH PASURUAN

Pandemi covid-19 mengakibatkan kegiatan sosial khususnya pendidikan dilakukan di rumah. Kegiatan pembelajaran dilakukan di rumah untuk mengurangi penyebaran covid-19, proses pembelajaran yang dilakukan di rumah ini membutuhkan pendampingan orang tua. Ada dua potensi yang diberikan ketika adanya pendampingan orang tua, dari segi positifnya orang tua dapat meningkatkan kedisiplinan anak saat belajar dan dari segi negatifnya jika orang tua kurang maksimal dalam mendampingi anak, anak dapat melakukan kegiatan yang tak terkendali. Terlebih lagi pada masa pandemi covid-19 sangat diperlukan perndampingan orang tua untuk proses belajar anak dan kegiatan lainnya. Penelitian ini bertujuan untuk mengetahui cara orang tua dalam strategi mendampingi anak belajar di rumah pada masa pandemi Covid-19. Penelitian ini menggunakan pendekatan deskriptif kuantitatif. Responden dalam penelitian ini sebanyak 30 orang tua. Pengumpulan data dilakukan menggunakan instrumen angket, analisis data bersifat deskriptif kuantitaif. Hasil penelitian menujukkan kurang optimal. Terbukti dari hasil rata-rata persentase 40% pada strategi orang tua dapat diartikan bahwa orang tua sudah mulai membiasakan anaknya untuk belajar di rumah dengan jadwal belajar yang sudah disepakati dan 37,13% pada mendampingi anak dapat diartikan bahwa orang tua telah melakukan pendampingan pada anaknya secara maksimal mulai dari kedisiplinan, tata krama, dan kemandirian

Sparse Modeling for Image and Vision Processing

In recent years, a large amount of multi-disciplinary research has been conducted on sparse models and their applications. In statistics and machine learning, the sparsity principle is used to perform model selection---that is, automatically selecting a simple model among a large collection of them. In signal processing, sparse coding consists of representing data with linear combinations of a few dictionary elements. Subsequently, the corresponding tools have been widely adopted by several scientific communities such as neuroscience, bioinformatics, or computer vision. The goal of this monograph is to offer a self-contained view of sparse modeling for visual recognition and image processing. More specifically, we focus on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.Comment: 205 pages, to appear in Foundations and Trends in Computer Graphics and Visio

PENGARUH MODIFIKASI PERMAINAN MONOPOLI TERHADAP PENINGKATAN KEMAMPUAN MENYELESAIKAN SOAL CERITA TERKAIT KONSEP BERHITUNG SISWA SD KELAS I: Penelitian Kuasi Eksperimen pada Siswa Kelas I Sekolah Dasar Kecamatan Lemahwungkuk Kota Cirebon

Penelitian ini dilatarbelakangi kurangnya kemampuan menyelesaikan soal cerita siswa sekolah dasar dalam materi bilangan, hal tersebut karena pembelajaran yang biasa digunakan kurang menarik. Berdasarkan hasil pengamatan di kelas, masih terdapat siswa yang tidak menyukai pelajaran matematika. Oleh karena itu dibutuhkan media pembelajaran yang menarik dan menyenangkan, tetapi dapat mendorong kemampuan menyelesaikan soal cerita siswa yaitu dengan media modifikasi permainan monopoli. Penelitian ini bertujuan untuk mengetahui pengaruh antara kemampuan menyelesaikan soal cerita terkait konsep berhitung siswa SD kelas I sebelum mengikuti pembelajaran dengan modifikasi permainan monopoli dan sesudah mengikuti pembelajaran dengan modifikasi permainan monopoli. Penelitian ini adalah penelitian kuasi eksperimen dengan desain penelitian menggunakan pretest-posttest control group design. Populasi penelitian ini adalah siswa kelas I di salah satu SDN Kecamatan Lemahwungkuk. Hasil analisis data pretest dan posttest kelas eksperimen menunjukkan adanya pengaruh modifikasi permainan monopoli terhadap kemampuan menyelesaikan soal cerita siswa SD kelas I. Nilai rata-rata pretest kelas eksperimen adalah 57,45 dan nilai rata-rata posttest kelas eksperimen adalah 82,45, sehingga rata-rata nilai siswa di kelas eksperimen mengalami peningkatan sebesar 25. Hasil analisis hipotesis kedua menunjukkan bahwa terdapat perbedaan kemampuan menyelesaikan soal cerita siswa yang menggunakan modifikasi permainan monopoli dan pembelajaran problem based learning. Rekomendasi pada penelitian ini adalah kemampuan menyelesaikan soal cerita terkait konsep berhitung siswa harus lebih dikembangkan lagi agar siswa lebih dapat mudah dalam menyelesaikan soal cerita untuk menyelesaikan soal dengan baik. -------- Modifikasi Permainan Monopoli, Kuasi Eksperimen. This research is motivated by the lack of ability to solve story problems of elementary school students in number material, this is because the learning that is usually used is not interesting. Based on observations in the classroom, there are still students who do not like math lessons. Therefore, an interesting and fun learning media is needed, but it can encourage the ability to solve students' story problems, namely with the modified media of the monopoly game. This study aims to determine the significant difference between the ability to solve story problems related to the concept of counting of grade I elementary school students before participating in learning with modified monopoly games and after participating in learning with modified monopoly games. This research is a quasi-experimental research with research design using pretest-posttest control group design. The population of this study were first grade students at one of the elementary schools in Lemahwungkuk District. The results of the pretest and posttest data analysis of the experimental class showed the effect of monopoly game modification on the ability to solve story problems of grade I elementary school students. The average value of the experimental class pretest was 57.45 and the average value of the experimental class posttest was 82.45, so that the average student score in the experimental class increased by 25. The results of the second hypothesis analysis show that there are differences in the ability to solve student story problems using modified monopoly games and problem-based learning. The recommendation in this study is that the ability to solve story problems related to students' counting concepts must be further developed so that students can more easily solve story problems to solve problems well

Ignatian education for social transformation in rural Ecuador

Catholic Social Teaching proclaims the integral human development of all, from basic necessities to collective and spiritual dimensions, as a basic principle of justice pre-announcing the justice of the Kingdom. It offers, however, no universal solution as to how to achieve this, recommending instead that each Christian community should devise its own solutions. The challenge of delivering a contextualized option for the most vulnerable thus falls to Catholic Social Praxis. Children suffer particularly harshly from poverty, which affects all dimensions of their lives and prevents them from developing their potentialities, thus determining the future of following generations. Education has a vital role to play in redressing this injustice and promoting social transformation. Religious orders and faith-based organizations have long accepted the challenge of forming the whole child in challenging situations. A teaching order such as the Society of Jesus, with its commitment to social justice, provides a perfect example of this in its praxis of educación popular in limit situations - in this case, a deprived area of the Ecuadorian Andes. The thesis first traces the Society’s understanding of mission since its foundation, and more particularly the evolution of its social apostolate in parallel with both Catholic Social Teaching and new secular concepts of human rights, justice and human development. It then turns to the Jesuit mission of education, exploring first Ignatius’s vision of education, then the impact of integrating notions of social responsibility and justice into the education apostolate. This evolution is explored with particular reference to Latin America: the work of St Alberto Hurtado in Chile; the emergence of educación popular; Paulo Freire’s method of conscientisation and the Latin American Bishops’ formulation of educación liberadora as liberation theology was emerging. The question marks raised by Juan Luis Segundo in connection with Freire’s methods highlight the theoretical and practical issues of educational justice in a continent where the disparity between the many and the privileged few remains stark. These issues are explored in connection with an example of the Society’s praxis of educación popular: the founding and expansion of Fe y Alegría. The complexities of the process highlight the need to assess the outcomes of such praxis for justice and transformation. A methodology involving a cycle of context analysis, planning, action and reflection will be used for the qualitative study of two Ignatian-inspired organizations working in the deprived central highlands of Ecuador. In the search for a potential tool to yield further, quantitative data the thesis turns to modern visions of justice and explores in particular the Capability Approach (CA) developed by Amartya Sen and Martha Nussbaum. The flexibility of the CA means that it can be adapted to provide quantitative data relating to an institution’s effectiveness in promoting collective as well as transcendental capabilities. This, as well as recent capability-based studies assessing the impact of NGOs on children’s development, leads to the conclusion that the CA is a suitable tool for a quantitative evaluation of the impact of Ignatian educación popular on all dimensions of children’s development. The various steps to be followed in the field in order to obtain these data are explained. The narrative then focusses on the case of three small rural Fe y Alegría schools offering formal education to indigenous children. The study begins with a thorough context analysis to establish the structures of living together and potential obstacles to individual and collective agency. The method used in the field is then described. Result analysis is based both on qualitative data (documents, participant observation, interviews) and on quantitative data from questionnaires to children and parents and children’s group work. The findings highlight a high level of adaptive preferences regarding basic necessities, as well as pervasive gender inequality, widespread violence and ambiguous results regarding participation and spirituality. Further reflection opens up onto wider issues: the effectiveness of contextualized Ignatian pedagogy in developing critical thinking and agency for change; the barriers placed on young women in particular by the structures of living together; the search for suitable curriculum models; the nature of ‘transforming spirituality’ and the future of Ignatian educación popular. It concludes that a full statement from the Magisterium would provide the basis of a complete, coherent system of justice for children

UNSUPERVISED CONVOLUTIONAL NEURAL NETWORKS FOR MOTION ESTIMATION

We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 GPU used for this research.We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 GPU used for this research.We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 GPU used for this research.Traditional methods for motion estimation estimate the motion field F between a pair of images as the one that minimizes a predesigned cost function. In this paper, we propose a direct method and train a Convolutional Neural Network (CNN) that when, at test time, is given a pair of images as input it produces a dense motion field F at its output layer. In the absence of large datasets with ground truth motion that would allow classical supervised training, we propose to train the network in an unsupervised manner. The proposed cost function that is optimized during training, is based on the classical optical flow constraint. The latter is differentiable with respect to the motion field and, therefore, allows backpropagation of the error to previous layers of the network. Our method is tested on both synthetic and real image sequences and performs similarly to the state-of-the-art methods