A Framework for Understanding Unintended Consequences of Machine Learning

As machine learning increasingly affects people and society, it is important that we strive for a comprehensive and unified understanding of potential sources of unwanted consequences. For instance, downstream harms to particular groups are often blamed on "biased data," but this concept encompass too many issues to be useful in developing solutions. In this paper, we provide a framework that partitions sources of downstream harm in machine learning into six distinct categories spanning the data generation and machine learning pipeline. We describe how these issues arise, how they are relevant to particular applications, and how they motivate different solutions. In doing so, we aim to facilitate the development of solutions that stem from an understanding of application-specific populations and data generation processes, rather than relying on general statements about what may or may not be "fair."Comment: 6 pages, 2 figures; updated with corrected figure

Analysis of User’s Opinion using Deep Neural Network Techniques

Through many research and discoveries it has been widely accepted that aspect-level sentiment classification is achieved effectively by using Long Short-Term Memory (LSTM) network combined with attention mechanism and memory module. As existing approaches widely depend on the modeling of semantic relatedness of an aspect, at the same time we ignore their syntactic dependencies which are already a part of that sentence. This will result in undesirably an aspect on textual words that are descriptive of other aspects. So, in this paper, to offer syntax free contexts as well as they should be aspect specific, so we propose a proximity-weighted convolution network. To be more precise, we have one way of determining proximity weight which is dependency proximity. The construction of the model includes bidirectional LSTM architecture along with a proximity-weighted convolution neural network

Analysis of User’s Opinion using Deep Neural Network Techniques

Through many research and discoveries it has been widely accepted that aspect-level sentiment classification is achieved effectively by using Long Short-Term Memory (LSTM) network combined with attention mechanism and memory module. As existing approaches widely depend on the modeling of semantic relatedness of an aspect, at the same time we ignore their syntactic dependencies which are already a part of that sentence. This will result in undesirably an aspect on textual words that are descriptive of other aspects. So, in this paper, to offer syntax free contexts as well as they should be aspect specific, so we propose a proximity-weighted convolution network. To be more precise, we have one way of determining proximity weight which is dependency proximity. The construction of the model includes bidirectional LSTM architecture along with a proximity-weighted convolution neural network

Third Eye for Blind using Ultrasonic Sensor

People with visual disabilities are often dependent on external assistance which can be provided by humans, trained dogs, or special electronic devices as support systems for decision making. The main problem with blind people is how to navigate their way to wherever they want to go. Such people need assistance from others with good eyesight. As described by WHO, 10% of the visually impaired have no functional eyesight at all to help them move around without assistance and safely. This project is designed to help the blind to overcome the lack of visual sense, by using other senses like sound and touch. The system uses Atmega-328 microcontroller, which is a high performance 8-bit AVR RISC-based microcontroller. For sensing the distance the system uses a HC-SR04, an Ultrasonic Range Finder Distance Sensor Module. The sensor module is designed to measure the distance using the principle of SONAR or RADAR, using ultrasonic wave to determine the distance of an object. The system also consists of a buzzer to generate an alarm sound and a motor to generate vibration signals. The system uses audio and vibration signals to notify the user about upcoming hurdle. As the distance between glove and obstacle decreases, frequency of both audio and vibration signals increases. Thus the system helps to ease the navigation process for the needy. This system offers a low-cost, reliable, portable, low power consumption and robust solution for navigation with obvious short response time

A Prospective Study of Comparing Immediate Versus Delayed Removal of Urinary Catheter following Elective Cesarean Delivery

OBJECTIVE: To compare the outcomes of immediate and delayed catheter removal of urinary catheter following elective cesarean section. STUDY DESIGN: In a prospective clinical trial at a university teaching hospital, 180 eligible women admitted for primary or repeat elective cesarean delivery were randomized into two equal groups. In group I, the catheter was removed 18-24 hours postoperatively, whereas in group II, the catheter was removed immediately after the procedure. RESULTS: The incidence of postoperative significant bacteriuria (p=<0.01), burning micturition, dysuria, frequency, urgency are comparatively lower in Group II than Group I. The mean postoperative ambulation time (p<0.001), first voiding time (p<0.001), duration of hospital stay (p<0.001) were also significantly shorter in group II. There was no significant difference between the two groups in the incidence of recatheterization CONCLUSION: Immediate removal of urinary catheter following elective cesarean section is associated with lower risk of urinary tract infection and earlier postoperative ambulation

Pengaruh Sistem Olah Tanah Dan Aplikasi Mulsa Bagas Pada Pertanaman Tebu (Saccharum Officinarum L.) Terhadap Populasi Mikroorganisme Pelarut Fosfat Di PT. GMP Lampung Tengah

Sugarcane plantation atPT Gunung Madu Plantation (GMP) has done intensive tillage since 1975. To maintain sustainable production and soil fertility is necessary to manage soil according to good soil conservation. The good choice to maintaince soil quality is no-tillage and mulching system. The research was carried out since July 2010,phosphate solubilizing microorganismwere observedat9 and 12 months after ratoon one, in April and July 2012. The research was designed as a split plot with a randomized block design (RBD) with 5 replications . Main plot are tillage system that consists of no-tillage (T0) and tillage (T1). The subplots were application of baggase mulch. Consisting ofwithout bagasse mulch application (M0) andwith 80 t ha-1baggase mulch (M1). Data were analyzed by analysis of variance at the level of 1% and 5%, which previously had been analyzed with the Bartlett test forHomogeneity and Additivity with Tukey test, and followed by LSD test at the level of 1% and 5%. The results showed that the tillage system and bagasse mulch application did not give significant effect on the population of phosphate solubilizing microorganism. Correlation test results showed that the phosphate solubilizing microorganism population has no correlation with organic C, total N, soil pH, soil moisture, soil temperature, and available P

Aorto-occlusive disease causing pregnancy complications: A serendipitous diagnosis

Takayasu arteritis or pulse-less disease is known to present in myriad forms. Here, we report the case of a 22-year-old young pregnant&nbsp;female who presented to us with pregnancy complications was finally diagnosed to have Takayasu Arteritis but not before her disease&nbsp;course took a lot of diagnostic turns. It highlights the fact that the disease is very variable in its presentation. The other unique&nbsp;presentations reported in literature along with a brief review of the treatment options are also given