Data-Driven Robust Beamforming for Initial Access

We consider a robust beamforming problem where large amount of downlink (DL) channel state information (CSI) data available at a multiple antenna access point (AP) is used to improve the link quality to a user equipment (UE) for beyond-5G and 6G applications such as environment-specific initial access (IA) or wireless power transfer (WPT). As the DL CSI available at the current instant may be imperfect or outdated, we propose a novel scheme which utilizes the (unknown) correlation between the antenna domain and physical domain to localize the possible future UE positions from the historical CSI database. Then, we develop a codebook design procedure to maximize the minimum sum beamforming gain to that localized CSI neighborhood. We also incorporate a UE specific parameter to enlarge the neighborhood to robustify the link further. We adopt an indoor channel model to demonstrate the performance of our solution, and benchmark against a usually optimal (but now sub-optimal due to outdated CSI) maximum ratio transmission (MRT) and a subspace based method.We numerically show that our algorithm outperforms the other methods by a large margin. This shows that customized environment-specific solutions are important to solve many future wireless applications, and we have paved the way to develop further data-driven approaches.Comment: 6 pages, 6 figures, Accepted in IEEE GLOBECOM 202

Resource Efficient Over-the-Air Fronthaul Signaling for Uplink Cell-Free Massive MIMO Systems

We propose a novel resource efficient analog over-the-air (OTA) computation framework to address the demanding requirements of the uplink (UL) fronthaul between the access points (APs) and the central processing unit (CPU) in cell-free massive multiple-input multiple-output (MIMO) systems. We discuss the drawbacks of the wired and wireless fronthaul solutions, and show that our proposed mechanism is efficient and scalable as the number of APs increases. We present the transmit precoding and two-phase power assignment strategies at the APs to coherently combine the signals OTA in a spectrally efficient manner. We derive the statistics of the APs locally available signals which enable us to to obtain the analytical expressions for the Bayesian and classical estimators of the OTA combined signals. We empirically evaluate the normalized mean square error (NMSE), symbol error rate (SER), and the coded bit error rate (BER) of our developed solution and benchmark against the state-of-the-art wired fronthaul based systemComment: 6 pages, 4 figures, Submitted to IEEE International Conference on Communications (ICC), 202

Synthesis and antimicrobial evaluation of substituted fluoroquinolones under conventional and microwave irradiation conditions

A series of new fluoroquinolones analogs (3a-i) were prepared under conventional and microwave irradiation technique. Ethyl 1-cyclopropyl-6,7-difluoro-8-methoxy-4-oxo-1,4-dihydroquinoline-3-carboxylate (1) on reaction with boric acid and acetic anhydride in the presence of catalytic amount of zinc chloride under reflux, resulted in an unstable borate complex. Which was instantaneously treated with morpholine, piperidine, thiomorpholine, 2,6-dimethylmorpholine, 4,5,6,7-tetrahydrothieno[3,2-c]pyridine hydrochloride, 5,6,7,7a-tetrahydrothieno[3,2-c]pyridin-2(4H)-one hydrochloride, 2,3-dichlorophenylpiperazine hydrochloride, 3-(piperidin-4-yl)benzo[d]isoxazole hydrochloride and 5,6,7,8-tetrahydro-[1,2,4] triazolo[4,3-a]pyrazine, in the presence of triethylamine to yield compounds 3a-i. The same compounds on the other hand synthesized using a microwave irradiation technique in the presence of triethylamine and adsorbed neutral alumina. The structures of the synthesized compounds were established on the basis of spectral and analytical data. The antimicrobial activity of newly synthesized compounds were evaluated against different microorganisms and found the compounds exhibited significant activity

ANALIZA KOLIZJI W RUCHU MIEJSKIM Z WYKORZYSTANIEM TECHNIK GŁĘBOKIEGO UCZENIA

Road accidents are concerningly increasing in Andhra Pradesh. In 2021, Andhra Pradesh experienced a 20 percent upsurge in road accidents. The state's unfortunate position of being ranked eighth in terms of fatalities, with 8,946 lives lost in 22,311 traffic accidents, underscores the urgent nature of the problem. The significant financial impact on the victims and their families stresses the necessity for effective actions to reduce road accidents. This study proposes a framework that collects accident data from regions, namely Patamata, Penamaluru, Mylavaram, Krishnalanka, Ibrahimpatnam, and Gandhinagar in Vijayawada (India) from 2019 to 2021. The dataset comprises over 12,000 records of accident data. Deep learning techniques are applied to classify the severity of road accidents into Fatal, Grievous, and Severe Injuries. The classification procedure leverages advanced neural network models, including the Multilayer Perceptron, Long-Short Term Memory, Recurrent Neural Network, and Gated Recurrent Unit. These models are trained on the collected data to accurately predict the severity of road accidents. The project study to make important contributions for suggesting proactive measures and policies to reduce the severity and frequency of road accidents in Andhra Pradesh.Liczba wypadków drogowych w Andhra Pradesh niepokojąco rośnie. W 2021 r. stan Andhra Pradesh odnotował 20% wzrost liczby wypadków drogowych. Niefortunna pozycja stanu, który zajmuje ósme miejsce pod względem liczby ofiar śmiertelnych, z 8 946 ofiarami śmiertelnymi w 22 311 wypadkach drogowych, podkreśla pilny charakter problemu. Znaczący wymiar finansowy dla ofiar i ich rodziny podkreśla konieczność podjęcia skutecznych działań w celu ograniczenia liczby wypadków drogowych. W niniejszym badaniu zaproponowano system gromadzenia danych o wypadkach z regionów Patamata, Penamaluru, Mylavaram, Krishnalanka, Ibrahimpatnam i Gandhinagar w Vijayawada (India) w latach 2019–2021. Zbiór danych obejmuje ponad 12 000 rekordów danych o wypadkach. Techniki głębokiego uczenia są stosowane do klasyfikowania wagi wypadków drogowych na śmiertelne, poważne i ciężkie obrażenia. Procedura klasyfikacji wykorzystuje zaawansowane modele sieci neuronowych, w tym wielowarstwowy perceptron, pamięć długoterminową i krótkoterminową, rekurencyjną sieć neuronową i Gated Recurrent Unit. Modele te są trenowane na zebranych danych w celu dokładnego przewidywania wagi wypadków drogowych. Projekt ma wnieść istotny wkład w sugerowanie proaktywnych środków i polityk mających na celu zmniejszenie dotkliwości i częstotliwości wypadków drogowych w Andhra Pradesh

URBAN TRAFFIC CRASH ANALYSIS USING DEEP LEARNING TECHNIQUES

Road accidents are concerningly increasing in Andhra Pradesh. In 2021, Andhra Pradesh experienced a 20 percent upsurge in road accidents. The state's unfortunate position of being ranked eighth in terms of fatalities, with 8,946 lives lost in 22,311 traffic accidents, underscores the urgent nature of the problem. The significant financial impact on the victims and their families stresses the necessity for effective actions to reduce road accidents. This study proposes a framework that collects accident data from regions, namely Patamata, Penamaluru, Mylavaram, Krishnalanka, Ibrahimpatnam, and Gandhinagar in Vijayawada (India) from 2019 to 2021. The dataset comprises over 12,000 records of accident data. Deep learning techniques are applied to classify the severity of road accidents into Fatal, Grievous, and Severe Injuries. The classification procedure leverages advanced neural network models, including the Multilayer Perceptron, Long-Short Term Memory, Recurrent Neural Network, and Gated Recurrent Unit. These models are trained on the collected data to accurately predict the severity of road accidents. The project study to make important contributions for suggesting proactive measures and policies to reduce the severity and frequency of road accidents in Andhra Pradesh

Chitin Binding Proteins Act Synergistically with Chitinases in Serratia proteamaculans 568

Genome sequence of Serratia proteamaculans 568 revealed the presence of three family 33 chitin binding proteins (CBPs). The three Sp CBPs (Sp CBP21, Sp CBP28 and Sp CBP50) were heterologously expressed and purified. Sp CBP21 and Sp CBP50 showed binding preference to β-chitin, while Sp CBP28 did not bind to chitin and cellulose substrates. Both Sp CBP21 and Sp CBP50 were synergistic with four chitinases from S. proteamaculans 568 (Sp ChiA, Sp ChiB, Sp ChiC and Sp ChiD) in degradation of α- and β-chitin, especially in the presence of external electron donor (reduced glutathione). Sp ChiD benefited most from Sp CBP21 or Sp CBP50 on α-chitin, while Sp ChiB and Sp ChiD had major advantage with these Sp CBPs on β-chitin. Dose responsive studies indicated that both the Sp CBPs exhibit synergism ≥0.2 µM. The addition of both Sp CBP21 and Sp CBP50 in different ratios to a synergistic mixture did not significantly increase the activity. Highly conserved polar residues, important in binding and activity of CBP21 from S. marcescens (Sm CBP21), were present in Sp CBP21 and Sp CBP50, while Sp CBP28 had only one such polar residue. The inability of Sp CBP28 to bind to the test substrates could be attributed to the absence of important polar residues

Parsing the Wiki collection and snippet generation

University of Minnesota M.S. thesis. April 2013. Major: Computer science. Advisor: Dr Donald Crouch. 1 computer file (PDF); vi, 31 pages.Information Retrieval (IR) is a feld which deals with retrieving useful information from large sets of data in response to a query. Much information in this digital age is stored in XML format, which associates a structure with a document. Though IR systems have been used for years to access documents, the field has greatly expanded with the emergence of the world wide web, which emphasizes the structure of the data. The amount of data makes the identification of various portion(s) of a document difficult; document structure helps in this task. This thesis describes a retrieval task known as snippet retrieval. A snippet is the smallest meaningful body of text which can be used to establish the relevance of the document without actually looking at the document. The work on snippet retrieval is extended from past work in focused retrieval, wherein a ranked list of focused elements is retrieved in response to the user query. The Vector Space Model provides the framework for retrieval; we use Smart for basic retrieval functions. Our system for dynamic element retrieval, Flex, enables us to identify and rank the individual elements of each hypertext document with respect to the query. We include a discussion of focusing strategies and the use of focused elements for snippet generation. Results of our top-ranked 2011 and 2012 Snippet Retrieval track runs are included

Injectable platelet-rich fibrin polymerized with hydroxyapatite bone graft for the treatment of three-wall intrabony defects: A randomized control clinical trial

Background: The study was aimed to compare and evaluate the clinical and radiographic outcomes of injectable platelet-rich fibrin (i-PRF) polymerized with hydroxyapatite (HA) bone graft and HA bone graft alone for treating three-wall intrabony defects (IBDs). Materials and Methods: The trial was planned as a randomized, prospective clinico-radiographic study with inclusion of 34 three-wall IBDs in patients with stage III periodontitis. IBDs were assigned randomly to one of the groups, i.e., Group I – experimental (i-PRF + HA) and Group II – control (HA alone). At baseline and 6 and 9-month intervals, both the clinical and radiographic measurements were taken and baseline and 9-month data were tabulated and imported into SPSS 22 software. Student unpaired and paired t- tests were used to find significant differences (p<0.05). Results: Both the groups showed substantial changes in all clinical and radiographic measures on comparison from baseline values. On intergroup comparison, the i-PRF + HA group reported significantly higher original defect resolution and original defect fill as compared to the HA group. Conclusion: i-PRF polymerized with HA graft has shown better results as compared to HA graft alone in three-wall IBDs and therefore can be used as a better possible alternative for the treatment of three-wall IBDs