Miracle-dz/UniFAR-FTUs huggingface dataset:
A Right to a Human Decision

Recent advances in computational technologies have spurred anxiety about a shift of power from human to machine decision-makers. From prison sentences to loan approvals to college applications, corporate and state actors increasingly lean on machine learning tools (a subset of artificial intelligence) to allocate goods and to assign coercion. Machine-learning tools are perceived to be eclipsing, even extinguishing, human agency in ways that sacrifice important individual interests. An emerging legal response to such worries is a right to a human decision. European law has already embraced the idea in the General Data Protection Regulation. American law, especially in the criminal justice domain, is already moving in the same direction. But no jurisdiction has defined with precision what that right entails, or furnished a clear justification for its creation. This Article investigates the legal possibilities of a right to a human decision. I first define the conditions of technological plausibility for that right as applied against state action. To understand its technological predicates, I specify the margins along which machine decisions are distinct from human ones. Such technological contextualization enables a nuanced exploration of why, or indeed whether, the gaps that do separate human and machine decisions might have normative import. Based on this technological accounting, I then analyze the normative stakes of a right to a human decision. I consider three potential normative justifications: (a) an appeal to individual interests to participation and reason-giving; (b) worries about the insufficiently reasoned or individuated quality of state action; and (c) arguments based on negative externalities. A careful analysis of these three grounds suggests that there is no general justification for adopting a right to a human decision by the state. Normative concerns about insufficiently reasoned or accurate decisions, which have a particularly powerful hold on the legal imagination, are best addressed in other ways. Similarly, concerns about the ways that algorithmic tools create asymmetries of social power are not parried by a right to a human decision. Indeed, rather than firmly supporting a right to a human decision, available evidence tentatively points toward a countervailing ‘right to a well-calibrated machine decision’ as ultimately more normatively wellgrounded. * Frank and Bernice J. Greenberg Professor of Law, University of Chicago Law School. Thanks to Faith Laken for terrific research aid. Thanks to Tony Casey, David Driesen, Lauryn Gouldin, Daniel Hemel, Darryl Li, Anup Malani, Richard McAdams, Eric Posner, Julie Roin, and Lior Strahilevitz for thoughtful conversation. Workshop participants at the University of Chicago, the University of Houston, and Syracuse University School of Law also provided thoughtful feedback. All errors are mine. Electronic copy available at: https://ssrn.com/abstract=3382521
Dialog Clustering: a Framework for Automatic Text Clustering

Despite the recent advances in Natural Language Processing techniques, when it comes to unsupervised applications, such as text clustering, many critical issues arise, as evaluating the results of an un-supervised algorithm or making an unsupervised algorithm work in an automatic fashion. In this research we propose an innovative framework based on machine learning for the creation of a system capable of addressing these critical issues. The framework consists of four main steps: a step for converting text into embedding, a step to reduce the dimensionality of the generated embedding, a step for clustering data and, ﬁnally, a step to evaluate the results obtained and selecting the best clustering produced. Each of these steps uses diﬀerent models equipped with a mechanism for identifying and automatically selecting hyperparameters. Our framework guarantees good performance in clustering text without an a-priori knowledge of the data. Observing the results it can be seen how the subdivisions of the dataset vary according to the models used in the diﬀerent steps of the proposed system and how groups focused on speciﬁc themes are identiﬁed.
NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE

(:EUC'E ~~)uld like to invite its members to attend t.his year's National ('onfcrcww on ilrtificial Int.elligence. August 2% 26. 1983 This t bird national conference. co-sponsored b>r the I;nivcrsity of Ylaryland and George Mashington I-nivcrsitv, proniot w research in tht field of artificial in&-ligrncc by bringing togct her individuals from government. industry and acwdcmia arid by providing a published record of the confcrcnw as procwding.~ The three principal parts of 4.1.11 83 \vill bc thv Twhnical program. the Tutorial program and the R&D Exhibit program. Two innovat.ions introduced this yw arc t hc Technology Transfer Symposium and t\vo Technical \zorkshops The Tcchnic~a.1 Program, slated for August 21 26. will prcwnt substantial. original research in an array of different .,I1 awas. such as kno\vledgc representation, expert systems, cognit ivc niodelling. problem solving and inference, vision, et (' In addition to the twhnical presentations. panels will disww 1Cading twhnical. philosophical, and economic issues rclcwnt to the field :\lso. a limited amount of space is being provided for individuals or groups interested in conducting small group Lzorkshops on ;\I-related topics during the Twh11ira1 program The Tutorial Program. scheduled for August 22 and the morning of August 23. is composed of six, four hour tutorial units For our rcadws who arc just becoming familiar with the different AI arcas of interwt , thr tutorial program is an excellent means of acquiring state-of-'-the-art kno\vledgc from leading experts in these areas This yrar's tutorial topics arc: The R&D Exhibit. Program, sch&uled for the cntirc wcrk of the conference, will present products of special inttwst to the AI community As in the past 1 university and industrial laboratories have been invit.ed to participat.cl in the ISx-hibit program Leading publishers and comput,er hardware manufacturers will have displays. Companics, academic and research laboratories. .U service organizat.ions and publishers interested in more specific det.ails on the A.-! 111 83 R&I) Exhibit Program can contact the ,4. &N officr for informat ion One innovation t,his year, the Technology-Transfer 'iym-posium,
The Levels of Heavy Metals in Pigeon Feathers in Different Areas of Ajmer City (Rajasthan): Feather as an Indicator

The objective of the study is to provide evidence that pigeon feathers are good bioindicator of environmental pollution with Pb as heavy metals and Cu, Cr and Zn as trace element. Samples of Columba livia were collected from urban, sub urban and rural areas in Ajmer city (Rajasthan). The metals analyzed include lead, copper, chromium and zinc by AAS (Atomic Absorption Spectrophotometry). The results divided primary, secondary and tail fathers according to its richness with metals in order : Primary > tail > secondary and the metals zinc >chromium> copper > lead respectively : The study showed that urban areas are the richest area with in Pb, Cu, Cr, Zn and considers feathers as the best monitor of air pollution in the study area.
Testing the robustness of two water distribution system layouts under changing drinking water demand

A drinking water distribution system (DWDS) is a critical and a costly asset with a long lifetime. Drinking water demand is likely to change in the coming decades. Quantifying these changes involves large uncertainties. This paper proposes a stress test on the robustness of existing DWDS under changing drinking water demands. The stress test investigates the effects of extreme but plausible demand scenarios on the network performance. Two layouts, one conventional looped designed for fire flows and one designed as a self-cleaning, were tested. For 12 demand scenarios, diurnal patterns were simulated with the end-use model SIMDEUM. The performance of the network was evaluated on three criteria: (1) network pressure, (2) water quality, and (3) continuity of supply. Although the self-cleaning layout had higher head losses, it performed better regarding water quality than the conventional layout. Both networks are robust to the extremities of drinking water demands. The stress test is useful to quantify the performance range of the DWDS. For non-Dutch locations, the criteria and scenarios can be adapted to local conditions
Isolated Pancreatic Metastases of Renal Cell Cancer: Genetics and Epigenetics of an Unusual Tumour Entity

Simple Summary The entity of isolated pancreatic metastases is very rare in metastatic renal cell carcinoma and is characterized by unusual features: 1. The isolated occurrence of pancreatic metastases itself; 2. the long interval between treatment of renal cell carcinoma and the occurrence of pancreatic metastases (9.6 years); 3. the frequent multiple occurrence of isolated pancreatic metastases (36%); and 4. the favourable prognosis after surgical therapy (5-year survival rate 75%). Some of the causes of this protracted course can already be traced back to specific genetic/epigenetic changes. Abstract Isolated pancreatic metastases of renal cell carcinoma (isPMRCC) are a rare manifestation of metastatic renal cell carcinoma (mRCC) characterized by two peculiarities: (1). The definite or at least long-term exclusive occurrence of metastases in the pancreas and (2). an unusual low tumour aggressiveness with slow tumour progression and consecutive, good treatment results. According to current knowledge, the exclusive occurrence of pancreatic metastases is due to a highly specific and highly selective seed and soil mechanism, which does not allow metastases settlement outside the pancreas, and whose detailed genetic/epigenetic causes are not yet elucidated. Recent studies have shed light on some of the pathways involved for the protracted course of the disease and highlighted a special genetic profile (lack of loss of 9p, lower weight genome instability index, low frequency of BAP1 alterations, and a high frequency of PBRM1 loss), which deviates from the conventional mRCC profile. Finally, the question of the reasons for the long-term relative genetic stability of the involved cell clones, which is an essential prerequisite for a favourable prognosis, remains unanswered.
Combined Processing of Hyperspectral and Thermal Images of Plants in Soil for the Early Diagnosis of Drought

The possibilities of explainable artificial intelligence (XAI) in the early diagnosis of drought in plants based on hyperspectral images (HSI) are investigated. To provide the explainability and high accuracy to the result, we used the markup of HSI by superimposed Thermal IR (TIR) images of the last day of the experiment. Traditional HSI-based NDVI (Normalized Difference Vegetation Index) images were also constructed. The markup of HSIs based on their clustering by the k-means method into 5 classes was also objectified: wet plants; plants in a state of drought; wet soil; dry soil; background. For HSI, on the day of the experiment started, the number of clusters was set to 2 less to reflect the absence of drought circumstances. For use in training and testing, all HSIs channels are marked up with the results of clustering. The HIS-TIR-combination made it possible to determine the temperature for each plant pixel in HSI, and as the result to determine the number of days without watering. A fully connected Double Layer Perceptron (DLP) neural network was used to solve classification and regression problems. The trained DLP-regressor showed the average accuracy of predicting the temperature of plants on the control days of the experiment RMSE = 0.52 degrees, providing an error in predicting the day of the beginning of the drought for near 2 days. The DLP-classifier was able to classify the drought of the plant in the early stages (the fifth day) with an accuracy of 97.3%. Software tools: pytorch, scikit-learn, pysptools.
DISRUPTIVE TECHNOLOGIES IN EDUCATION: A REVIEW

: Disruptive technologies in recent education system cannot be denied. Technology transformation in education system provides students a cost effectively scale education. This paper reviews the research on the subject of disruptive technologies in education and found that many disruptive technologies are there such as Online resources, internet of things, virtual reality, artificial intelligence etc. that have important impact on higher education system around the world. These technologies are now widely used to support learning and teaching. Use of ICT helps students to reach the resources which they need in their learning process. Online delivery of different courses such as MOOCs at lower cost makes it easy for employees also to combine work and training. Mobile technology is also useful not only for learners but also for teachers to connect with the students from anywhere, anytime that makes learning more collaborative and effective. However some studies found some negative results also as huge investment is needed to implement these techniques in higher education system.
Composition of Cyberattack Models

Cyberattacks are threats that every system developer and administrators need to be familiar with. The use of Petri Nets to model cyberattacks has been shown to provide additional knowledge on the planning stages of defense systems. There have been several proposed extensions to a Petri Net model to accommodate the simulation of these attacks. Petri Nets with Players, Strategies, and Cost was recently proposed to model individual cyberattacks on systems. This study introduces the formalism required to compose individual Petri Nets with Players, Strategies, and Cost models from a single system attack to a full system, which may include different methods of attacks being attempted, modeling a more realistic situation. The model composition described includes the sequential and parallel possibilities of multiple attacks. An example of a possible attack scenario is described in order to demonstrate the practical application of the current results.
Corrigendum: Interactive influence of ENSO and IOD on contiguous heatwaves in Australia (2022 Environ. Res. Lett. 17 014004)

We identified an error in calculating the result shown in figure 7 of our recent letter Reddy et al (2021). The error affected the composite difference of detrended mean sea level pressure (MSLP) and geopotential height at 500 hPa (z500) between the strong El Niño (Es), strong El Niño co-occurring with strong Indian Ocean Dipole (IOD) positive (Es−Ips), strong El Niño co-occurring with moderate IOD positive (Es−Ipm), strong La Niña co-occurring with strong IOD negative (Ls−Ins) phases and neutral (El Niño– Southern Oscillation (ENSO) neutral+ IOD neutral; NN) phase, respectively. This also affected the associated text in the last paragraph of subsection 3.3 of our letter. However, the main conclusions of the letter are not influenced by this error. We reproduce figure 7 using the correct data, shown below. In subsection 3.3 physical mechanisms, the last paragraph’s first two sentences are the same, and the remaining text should read as follows. ‘The Es, Es−Ips, and Es−Ipm phases show positive changes in MSLP (figures 7(a)–(c)) and z500 (figures 7(e)–(g)) whole over Australia and along its northwest over the Indian Ocean, northeast over the Pacific Ocean, and negative changes along the southeast of Australia over the Tasman. These positive and negative changes of MSLP and z500 are stronger, particularly during the Es−Ips, and Es−Ipm phases compared to the Es. The MSLP and z500 changes during the Ls−Ins phase (figures 7(d) and (h)) are opposite to those in Es, Es−Ips, and Es−Ipm. However, these differences during the Ls−Ins phase are only significant along the northwest of Australia over the Indian Ocean. The high-pressure circulation features observed over Australia and along its northeast, north, and northwest coasts during the Es, Es−Ips, and Es−Ipm phases are associated with abnormal subsiding motion over those regions and favours anomalously low rainfall conditions (Cai et al 2011, 2012). These high-pressure conditions with reduced rainfall promote a favourable environment for developing and amplifying heatwaves over Australia (Perkins et al 2015, Loughran et al 2019). Hence, the increased geopotential height and the anticyclonic circulation features near Australia associated with the Es, Es−Ips, and Es−Ipm phases influence the contiguous heatwaves in Australia’. In the abstract, the penultimate sentence should read as ‘During the Es, Es−IPm, and Es−IPs seasons, the large-scale physical mechanisms are characterised by anticyclonic highs over much of Australia and along its northeast, north, and northwest coasts, favouring the occurrence and intensification of heatwaves in Australia’. In the conclusions section, the middle sentence (i.e. fifth) should read as ‘These phases (Es, Es−Ips, and Es−Ipm) are associated with the anomalous highpressure circulation patterns over and around Australia (anticyclonic pressure anomaly along northeast Australia over the Pacific Ocean and northwest over the Indian Ocean), which provides the favourable environment for the heatwaves’.
Sistem Pendukung Keputusan Kredit Usaha Rakyat PT. Bank Rakyat Indonesia Unit Kaliangkrik Magelang

Banyak faktor dan variabel yang mempengaruhi risiko kredit dalam pengambilan keputusan pada permasalahan Kredit Usaha Rakyat (KUR). Faktor-faktor yang digunakan sebagai dasar penilaian Kredit Usaha Rakyat pada PT.Bank Rakyat Indonesia Unit Kaliangkrik menggunakan prinsip dasar yang dikenal dengan prinsip “5 of Credit” yaitu Character, Capacity, Capital, Condition dan Collateral. Dari factor-faktor yang digunakan sebagai dasar penilaian kredit, digunakan metode Mining Classification Rule dalam membuat Sistem Pendukung Keputusan pemberian KUR. Terdapat beberapa algoritma yang dapat digunakan dalam data mining untuk metode klasifikasi salah satunya adalah algoritma k-nearest neightbor. Konsep sistem pendukung keputusan pemberian KUR ini dirancang dapat melakukan klasifikasi terhadap objek berdasarkan data pembelajaran yang jaraknya paling dekat dengan objek tersebut dan memberikan solusi nasabah yang layak menerima KUR berdasarkan masukan dari user dengan menggunakan metode k-nearest neighbors (knn). Data-data transaksi pembayaran nasabah lama akan dijadikan sebagai data training dimana sebelumnya akan ditentukan kelasnya terlebih dahulu. Penentuan kelas dilakukan dengan proses klasifikasi data berdasarkan kategori status nasabah sesuai jumlah tunggakan pembayaran kreditnya. Dari hasil perhitungan kemiripan kasus antara data calon nasabah baru dengan nasabah lama atau data training menggunakan algoritma K-Nearest Neighbor, hasil dengan nilai tertinggi akan dijadikan acuan seorang decision maker dalam mengambil keputusan. Many factors and variables that affect credit risk in decision-making on issues People's Business Credit (KUR). The factors are used as the basis of assessment of the People's Business Credit Unit at PT Bank Rakyat Indonesia Kaliangkrik using basic principle known as the principle of "5 of Credit" ie Character, Capacity, Capital, Collateral Condition and. Of the factors that are used as a basis for credit assessment, Classification Rule Mining method used in making the administration of KUR Decision Support Systems. There are several algorithms that can be used in data mining for classification methods one of which is the k-nearest algorithm neightbor. The concept of the provision of decision support system is designed KUR can perform the classification of objects based on distance learning data that is closest to the object and provide a viable solution customers receive KUR based on input from the user by using the k-nearest neighbors (KNN). Payment transaction data will be used as a customer long training data which will be determined prior to first class. Grading is done with the data classification process based on customer status categories according to the amount of credit outstanding payments. From the calculation of the similarity between the case of data with prospective new customers or old customers training data using the K-Nearest Neighbor algorithm, the results with the highest scores will be used as a reference to a decision maker in making decisions.
Using prototype-defined checkerboards to investigate the mechanisms contributing to the Composite Face Effect

We report the results from two experiments (n=192) examining the congruency effect (better performance for congruent vs incongruent stimuli) for prototype-defined checkerboard composites. We used a complete matching task design as that used to study a robust index of face recognition i.e., the composite face effect. The results from both experiments reveal an effect of order of presentation for congruent and incongruent trials. Critically, participants presented with incongruent first and then congruent trials revealed a significant congruency effect. In contrast, participants presented with congruent first and then incongruent trials showed no congruency effect. These results contribute to the composite effect literature by reporting the first evidence of a congruency effect for artificial non-face stimuli which do not have a predefined orientation. Also, they provide evidence in support of test order as a determining factor potentially modulating the composite effect.
Diabetic Retinopathy Detection: An App

Diabetic Retinopathy (DR) is an eye disease caused due to constant diabetes and it found to be the main cause of blindness young generation in any nation. Today, around 415 million people are living with diabetes from which 285 million people is currently suffering from DR (Diabetic Retinopathy) a complication of diabetes which affect the eye. Most of the people are not aware that diabetes can also be the reason of their visionoriented problems. DR have 3 features: Micro aneurysms (MAs), Hemorrhages (HMs) and Exudates (EXs). Which can be detected from a retinal image of patient known as Fundus image. This paper explains the disease, it’s features and throw light on the method we have applied for detection of Exudates and Hemorrhages. KeywordsMicroaneurysms, Hemorrhages, Exudates, Image processing, Morphological operation, CNN