From Statistical to Geolinguistic Data: Mapping and Measuring Linguistic Diversity

The aim of this paper is describing a new methodology for mapping and measuring linguistic diversity in a territory. The three methods that have been created by the Centro di eccellenza della ricerca Osservatorio linguistico permanente dell’italiano diffuso fra stranieri e delle lingue immigrate in Italia at the Università per Stranieri di Siena are the following: - the Toscane favelle model, a procedural application which passes from quantitative statistical data to a demolinguistic paradigm; - the Monterotondo-Mentana model. The surveys of quantitative and qualitative data are carried out using traditional tools (questionnaires, audio and video recordings) as well as advanced technologies; - the Esquilino model. Digital maps are created which present the distribution of the immigrant languages through the presence of signs in linguistic landscape. The final objective is putting together the data surveyed by the three methods in order to have a “speaking” territory, in which each point surveyed identifies the languages spoken and the various linguistic manifestations.Language Contact, Linguistic Diversity, Immigrant Languages, Geolinguistic Data, New Methodologies in Sociolinguistic Research

Binary Hypothesis Testing Game with Training Data

We introduce a game-theoretic framework to study the hypothesis testing problem, in the presence of an adversary aiming at preventing a correct decision. Specifically, the paper considers a scenario in which an analyst has to decide whether a test sequence has been drawn according to a probability mass function (pmf) P_X or not. In turn, the goal of the adversary is to take a sequence generated according to a different pmf and modify it in such a way to induce a decision error. P_X is known only through one or more training sequences. We derive the asymptotic equilibrium of the game under the assumption that the analyst relies only on first order statistics of the test sequence, and compute the asymptotic payoff of the game when the length of the test sequence tends to infinity. We introduce the concept of indistinguishability region, as the set of pmf's that can not be distinguished reliably from P_X in the presence of attacks. Two different scenarios are considered: in the first one the analyst and the adversary share the same training sequence, in the second scenario, they rely on independent sequences. The obtained results are compared to a version of the game in which the pmf P_X is perfectly known to the analyst and the adversary

A DESCRIPTIVE STUDY ON PREGNANCY AND CHILDBIRTH OF ONE STUDENT ONE CLIENT (OSOC) PATIENTS OF MIDWIFERY STUDENTS OF POLYTECHNIC BANJARNEGARA

Maternal Mortality Rate (MMR) and Infant Mortality Rate (MMR) are indicators of a country's welfare. In 2018 there were 421 maternal mortality cases in central java. This number was a decrease compared to the mortality case in 2017, as many as 475 cases.  This study aimed to identify health conditions during pregnancy and the childbirth period of the patients of One Student One Client (OSOC) in Polytechnic Banjarnegara. A descriptive study conducted at Basic Emergency Neonatal Obstetric Services (PONED) in Banjarnegara District in March - April 2019 to 26 pregnant women. The results showed that most of the respondents classified the low-risk age group as 21 respondents (81%). There are 15  respondents (58%) classified to low-risk pregnancy distance category, 24 respondents (92%) are classified to normal gestational age category, and average birth weight category. It is recommended to ensure maternal health during pregnancy and childbirth is always well monitored. Ensuring mothers can access quality services in health services. It is necessary to have continuous assistance from students in OSOC activities as an extended arm of health workers. Keywords: Pregnancy, Childbirth, Health Client

A QUALITATIVE STUDY: THE MANAGEMENT OF DIARRHEA AMONG TODDLERS

Diarrhea is a prime cause of morbidity in infants. Early in 2018, There were 141 cases in Beji Village, Banjarmangu Sub-district. The government had an effort to prevent diarrhea, one of which is by conducting socialization to the community. Mothers' knowledge of diarrhea disease needs has a significant influence in suppressing diarrhea. This study aimed to identify community points of view about the classification, prevention, and treatment of diarrhea. This study used a qualitative study method. Data Collected by Depth interview with 13 people in Beji Village, Banjarmangu Sub-district, Banjarnegara District. The results showed that the community had a different classification between diarrhea and 'luganen'. Diarrhea considered a disease, and luganen is a sign of growth and development. Diarrhea prevents by maintaining a clean and healthy lifestyle. Diarrhea treats using a mixture of guava leaves and turmeric as first aid. The infant will be brought to health facilities when the symptoms appear and become severer.Keywords: Local knowledge, prevention, treatment, diarrhe

A new Backdoor Attack in CNNs by training set corruption without label poisoning

Backdoor attacks against CNNs represent a new threat against deep learning systems, due to the possibility of corrupting the training set so to induce an incorrect behaviour at test time. To avoid that the trainer recognises the presence of the corrupted samples, the corruption of the training set must be as stealthy as possible. Previous works have focused on the stealthiness of the perturbation injected into the training samples, however they all assume that the labels of the corrupted samples are also poisoned. This greatly reduces the stealthiness of the attack, since samples whose content does not agree with the label can be identified by visual inspection of the training set or by running a pre-classification step. In this paper we present a new backdoor attack without label poisoning Since the attack works by corrupting only samples of the target class, it has the additional advantage that it does not need to identify beforehand the class of the samples to be attacked at test time. Results obtained on the MNIST digits recognition task and the traffic signs classification task show that backdoor attacks without label poisoning are indeed possible, thus raising a new alarm regarding the use of deep learning in security-critical applications

Privacy-Aware Processing of Biometric Templates by Means of Secure Two-Party Computation

The use of biometric data for person identification and access control is gaining more and more popularity. Handling biometric data, however, requires particular care, since biometric data is indissolubly tied to the identity of the owner hence raising important security and privacy issues. This chapter focuses on the latter, presenting an innovative approach that, by relying on tools borrowed from Secure Two Party Computation (STPC) theory, permits to process the biometric data in encrypted form, thus eliminating any risk that private biometric information is leaked during an identification process. The basic concepts behind STPC are reviewed together with the basic cryptographic primitives needed to achieve privacy-aware processing of biometric data in a STPC context. The two main approaches proposed so far, namely homomorphic encryption and garbled circuits, are discussed and the way such techniques can be used to develop a full biometric matching protocol described. Some general guidelines to be used in the design of a privacy-aware biometric system are given, so as to allow the reader to choose the most appropriate tools depending on the application at hand

An Improved Statistic for the Pooled Triangle Test against PRNU-Copy Attack

We propose a new statistic to improve the pooled version of the triangle test used to combat the fingerprint-copy counter-forensic attack against PRNU-based camera identification [1]. As opposed to the original version of the test, the new statistic exploits the one-tail nature of the test, weighting differently positive and negative deviations from the expected value of the correlation between the image under analysis and the candidate images, i.e., those image suspected to have been used during the attack. The experimental results confirm the superior performance of the new test, especially when the conditions of the test are challenging ones, that is when the number of images used for the fingerprint-copy attack is large and the size of the image under test is small.Comment: submitted to IEEE Signal Processing Letter

Distance Measures for Reduced Ordering Based Vector Filters

Reduced ordering based vector filters have proved successful in removing long-tailed noise from color images while preserving edges and fine image details. These filters commonly utilize variants of the Minkowski distance to order the color vectors with the aim of distinguishing between noisy and noise-free vectors. In this paper, we review various alternative distance measures and evaluate their performance on a large and diverse set of images using several effectiveness and efficiency criteria. The results demonstrate that there are in fact strong alternatives to the popular Minkowski metrics