Automatic inspection of analog and digital meters in a robot vision system

A critical limitation of most of the robots utilized in industrial environments arises due to their inability to utilize sensory feedback. This forces robot operation into totally preprogrammed or teleoperation modes. In order to endow the new generation of robots with higher levels of autonomy techniques for sensing of their work environments and for accurate and efficient analysis of the sensory data must be developed. In this paper detailed development of vision system modules for inspecting various types of meters, both analog and digital, encountered in a robotic inspection and manipulation tasks are described. These modules are tested using industrial robots having multisensory input capability

Carrier Frequency Offset Estimation Algorithm in the Presence of I/Q Imbalance in OFDM Systems

In this paper, we analyzed the feasibility of using a virtual carrier based carrier frequency offset estimation algorithm in the presence of I/Q imbalance in OFDM systems. Based on the analysis of the signal model with both receiver CFO and I/Q imbalance impairment we conclude that it is feasible to extending the virtual carrier based CFO estimation algorithm to the I/Q imbalance scenario. The CFO estimation performance is evaluated through computer simulation. Impact of parameters on the estimation performance is investigated and it is consistent with our analysis. After CFO correction, a blind based I/Q imbalance estimation and compensation algorithm is applied. The final detection performance demonstrates that the virtual carrier based CFO estimation performance is good enough for subsequent I/Q imbalance estimation and compensation

BENTHIC FORAMINIFERAL AND ITS ENVIRONMENTAL DEGRADATION STUDIES BETWEEN THE TSUNAMIGENIC SEDIMENTS OF MANDAPAM AND TUTICORIN, SOUTH EAST COAST OF INDIA

The Gulf of Mannar is a transitional zone between the Arabian Sea and Indian Ocean proper and is connected with the Bay of Bengal through a shallow sill, the Palk Strait. The study area extends from Mandapam to Tuticorin on the southern coast of Tamil Nadu (India) over a distance of 120 km. It is bound in the northeast by Rameshwaram Island, in the east by the Bay of Bengal, in the west by the Eastern and Western Ghats, and in the south by Tuticorin. A total of 36 sediment samples were collected from the beach (6) and the offshore (30) area in the study region. The offshore samples were collected at six transects keeping the stations at Mandapam (5 nos), Valinokkam (5 nos), Vaippar (5 nos), Vembar (5 nos), Kallar, (5 nos) and Tuticorin (5 nos). Totally, 77 benthic foraminiferal species (Post-tsunami) and varieties belonging to 39 genera, 13 families, 10 superfamilies and 4 suborders have been reported and illustrated. The following species are widely distributed in the pre and post-tsunami samples namely Spiroloculina communis, Quinqueloculina elongatum, Q.lamarckiana, Q. seminulum, Triloculina trigonula, Cibicides lobatululs, Ammonia beccarii, A. dentata, A.tepida, Elphidium crispum and Assilina ammonoides. Grain size studies shows the frequency curves vary from unimodal to bimodal in places of river discharge from the Vembar, Kallar, Vaippar and Tamiraparani, as a result of which an additional sub-population is deposited. At Mandapam and Tuticorin, the total species are increasing in the deeper depths whereas in Kallar there will be reverse trend which decreases with depth. Similarly, the living species also have the same trend at Vallinokkam. The scatter plot of salinity versus living species shows a positive correlation. The scatter plot of organic matter versus living species shows strong negative correlation and positive correlation with dead species showing a negative relation with the biomass. Further, the trend of organic matter vs. carbonate indicates that the littoral drift of sediments brought foraminifera from the inner shelf regions and has played a great role in the contribution of dead species, as well as microfossils. The present study indicated that the sediments were brought from the inner shelf

Priprava i evaluacija dvofazičnih plutajućih tableta fenoverina

A biphasic gastroretentive drug delivery system of fenoverine was developed to maintain constant plasma concentration. The delivery system consisted of a loading-dose tablet and a floating multiple matrix tablet prepared by the direct compression process. The drug release from biphasic GRDDS in 0.1 mol L1 HCl and SGF (enzyme free) was sustained over 12 h with buoyant properties. Stability studies showed no significant change in dissolution profiles (f2 value > 50). Based on the release kinetics, it can be concluded that the floating multiple matrix tablet containing HPMC was a particularly suitable gastroretentive drug delivery system with a zero-order release profile.U radu je opisan razvoj bifazičnog sustava za isporuku fenoverina s produljenim zadržavanjem u želucu radi održavanja konstantne koncentracije lijeka u plazmi. Sustav je dobiven metodom izravne kompresije, a sastoji se od tablete za inicijalno doziranje i matriksne tablete za plutanje. Oslobađanje lijeka iz bifazičnog GRDDS u 0,1 mol L1 HCl i SGF (bez enzima) bilo je produljeno više od 12 h, a sustav je pokazao plutajuća svojstva. Ispitivanja stabilnosti pokazala su da nema značajne promjene u profilu oslobađanja (f2 > 50). Na temelju kinetike oslobađanja može se zaključiti da su plutajuće višeslojne matriksne tablete s HPMC posebno pogodan sustav za isporuku fenoverina u želucu s kinetikom oslobađanja nultog reda

The Misuse of AUC: What High Impact Risk Assessment Gets Wrong

When determining which machine learning model best performs some high impact risk assessment task, practitioners commonly use the Area under the Curve (AUC) to defend and validate their model choices. In this paper, we argue that the current use and understanding of AUC as a model performance metric misunderstands the way the metric was intended to be used. To this end, we characterize the misuse of AUC and illustrate how this misuse negatively manifests in the real world across several risk assessment domains. We locate this disconnect in the way the original interpretation of AUC has shifted over time to the point where issues pertaining to decision thresholds, class balance, statistical uncertainty, and protected groups remain unaddressed by AUC-based model comparisons, and where model choices that should be the purview of policymakers are hidden behind the veil of mathematical rigor. We conclude that current model validation practices involving AUC are not robust, and often invalid

Climate change effects on Chickpea yield and its variability in Andhra Pradesh, India

Farmers usually do not know the precise output that is affected by climatic factors such as temperature and rainfall and are characterized by inter-annual variability, part of which is caused by global climate change. No study covers the influences of climate factors on yield and yield risk in the context of chickpea farming in Andhra Pradesh, India. In this context, this study aimed to investigate the trends in climate change variables during Rabi season (October to January, 1996-2020) and evaluated their variability on chickpea yields across different agro-climatic zones in Andhra Pradesh by employing Just and Pope production function. Four non-parametric methods-Alexandersson’s Standard Normal Homogeneity Test, Buishand’s Range Test, Pettitt’s Test and Von Neumann’s Ratio Test are applied to detect homogeneity in the data. Mann–Kendall (MK) test and Sen’s slope (SS) method were employed to analyze monthly rainfall trends and minimum and maximum temperature trends. Results of Just and Pope (panel data) quadratic and Cobb-Douglas methods revealed that monthly minimum temperature positively influenced the mean yield of chickpea (0.22% and 0.16%, respectively). However, rainfall (-0.41% and -0.31%) and maximum temperature (-0.08% and -0.04%) negatively influenced the mean yield of chickpea under quadratic and Cobb-Douglas models, respectively. Accordingly, rainfall (0.08% and 0.06%) and maximum temperature (0.83% and 0.72%) positively influenced the yield variability and minimum temperature (-0.77% and -0.67%) reduced yield variability of chickpea under quadratic and Cobb-Douglas models respectively. In view of these findings, it is imperative to advocate the farmers about the importance of cultivating drought-tolerant chickpea varieties, drought-proofing and mitigation strategies, micro-irrigation practices and improving their access to agro-meteorological information towards sustainable chickpea cultivation in Andhra Pradesh