Effect of cross wind on aerodynamic coefficients of ground vehicles.

The present work investigates the variation of aerodynamic coefficients with the change in the angle of flow. A mathematical equation has been developed for predicting the aerodynamic coefficients, when a vehicle is subjected to crosswind. A tractor-trailer model has been utilised to demonstrate the effectiveness of the proposed equations. Flow analysis was carried out using Computational Fluid Dynamics (CFD) software. CFD simulations have been carried out on the tractor-trailer model at a wind speed of 25 m/s, for wind angles ranging from 0 to 180. The computational results obtained have been used for comparing the predicted aerodynamic coefficients. This mathematical model developed can be used for various aerodynamic investigations that involve large angles of attack

Legislative Language For Success

Legislative committee meetings are an integral part of the lawmaking process for local and state bills. The testimony presented during these meetings is a large factor in the outcome of the proposed bill. This research uses Natural Language Processing and Machine Learning techniques to analyze testimonies from California Legislative committee meetings from 2015-2016 in order to identify what aspects of a testimony makes it successful. A testimony is considered successful if the alignment of the testimony matches the bill outcome (alignment is For and the bill passes or alignment is Against and the bill fails). The process of finding what makes a testimony successful was accomplished through data filtration, feature extraction, implementation of classification models, and feature analysis. Several features were extracted and tested to find those that had the greatest impact on the bill outcome. The features chosen provided information on the sentence complexity and type of words used (adjective, verb, nouns) for each testimony. Additionally all the testimonies were analyzed to find common phrases used within successful testimonies. Two types of classification models were implemented: ones that used the manually extracted feature as input and ones that used their own feature extraction process. The results from the classification models and feature analysis show that certain aspects within a testimony such as sentence complexity and using specific phrases significantly impact the bill outcome. The most successful models, Support Vector Machine and Multinomial Naive Bayes, achieved an accuracy of 91.79\% and 91.22\% respectivel

Creating a Portable Wireless Display

Real time computing has become a vital part in military applications. Moreover certain operations require that the soldiers carry computing devices to assist them. These devices, besides providing them with location-based information, should also be transmitting the requested data. In this thesis, we present a portable wireless display prototype, which renders the desktop of a remote computer. The prototype functions under the range of an 802.11b or Bluetooth wireless network. The Software interfacing is done with Virtual Network Computing (VNC). This thesis is a first step towards analyzing and creating head/wrist mounted displays capable of transmitting images from a remote computer. The thesis starts with an overview and proceeds with a discussion on the concepts involved behind the functioning of the prototype. It then provides a detailed description of the how the prototype was built, followed by a performance test and its analysis and concludes by summarizing the results achieved

Creating a Portable Wireless Display

Real time computing has become a vital part in military applications. Moreover certain operations require that the soldiers carry computing devices to assist them. These devices, besides providing them with location-based information, should also be transmitting the requested data. In this thesis, we present a portable wireless display prototype, which renders the desktop of a remote computer. The prototype functions under the range of an 802.11b or Bluetooth wireless network. The Software interfacing is done with Virtual Network Computing (VNC). This thesis is a first step towards analyzing and creating head/wrist mounted displays capable of transmitting images from a remote computer. The thesis starts with an overview and proceeds with a discussion on the concepts involved behind the functioning of the prototype. It then provides a detailed description of the how the prototype was built, followed by a performance test and its analysis and concludes by summarizing the results achieved

PENGARUH KONSENTRASI AUKSIN DALAM HYDROPRIMING BENIH CABAI KADALUARSA TERHADAP VIABILITAS BENIH DAN PERTUMBUHAN BIBIT

Belangie Tuahte Gundala. 1405101050042. Pengaruh Konsentrasi Auksin DalamHydropriming Benih Cabai RINGKASANCabai -1tahun-1namun produktivitas cabai tahun2016 mengalami penurunan sebesar 8,47 ton ha-1tahun-1atau terjadi penurunan sebesar2,05%. Penurunan produktivitas cabai di Indonesia salah satunya dikarenakan petani masihmenggunakan benih yang tidak bermutu. Pada dasarnya, benih merupakan organismehidup yang mutlak mengalami proses kemunduran dan akhirnya mati. Proses kemunduranbenih tidak dapat dicegah dan tidak dapat kembali namun dapat diperlambat denganperlakuan tertentu. Hydropriming adalah salah satu teknik peningkatan viabilitas benihmelalui proses hidrasi-dehidrasi benih dengan cara perendaman benih di dalam air untukkelangsungan proses metabolik menjelang perkecambahan benih. Penelitian ini bertujuanuntuk mengetahui pengaruh konsentrasi auksin dan tingkat kadaluarsa serta interaksi antarakonsentrasi auksin dan tingkat kadaluarsa terhadap viabilitas benih dan pertumbuhan bibitcabai yang telah mengalami kemunduran.Penelitian ini menggunakan Rancangan Acak Lengkap 0= 0 g L-1air, K1= 2 g L-1air, K2= 4 g L-1air, dan K3= 6 g L-1air. Faktor keduayaitu tingkat kadaluarsa 1= 4 bulan, T= 8 bulan danT= 12 bulan. Dengan demikian terdapat 12 kombinasi perlakuan. Masing-masingkombinasi perlakuan diulang sebanyak tiga kali, sehingga terdapat 36 satuan percobaan.Parameter viabilitas yang diamati adalah potensi tumbuh maksimum 3Aplikasi Perlakuan diawali dengan menimbang berat awal benih dengan timbangananalitik, setelah itu benih dimasukkan ke dalam erlenmeyer dan direndam dalam 1 Liter2aquades dengan menambah Indole Acetid Acid Hasil penelitian ini menunjukkan bahwa perlakuan konsentrasi auksin 2 g Lsecaraefektif mampu meningkatkan viabilitas benih dan pertumbuhan bibit cabai kadaluarsaberdasarkan nilai tolok ukur potensi tumbuh maksimum, daya berkecambah, indeks vigor,keserempakan tumbuh, dan kecepatan tumbuh relatif, panjang akar primer, bobotbrangkasan segar dan bobot brangkasan kering. Tingkat kadaluarsa 4 bulan secara efektifmampu meningkatkan viabilitas benih dan pertumbuhan bibit cabai kadaluarsa dilihatberdasarkan nilai tolok ukur potensi tumbuh maksimum dan daya berkecambah, bobotbrangkasan kering dan tinggi bibit pada 7 HSPT. Interaksi antara konsentrasi auksin 2 g Ldan tingkat kadaluarsa 4 bulan secara efektif mampu meningkatkan nilai potensi tumbuhmaksimum dan tinggi bibit pada 7 HSPT, konsentrasi auksin 2 g L-1dan tingkat kadaluarsa8 bulan secara efektif meningkatkan nilai tinggi tanaman pada 7 HSPT dan konsentrasiauksin 0 g L-1dan tingkat kadaluarsa 4 bulan secara efektif meningkatkan nilai tinggi 14HSPT.-1-

Phytocomplexity: Implications For Development Of Novel Anticancer Therapeutics Using Dietary Agents

Chemotherapy, employing single-molecule or multidrug concoctions inspired by the diverse repository of plant chemicals, has been the mainstay of cancer treatment for years. However, isolating single molecules has proven to be expensive along with limited therapeutic window and toxicity. On the other hand, whole foods, while preserving the natural complex balance between their constituent phytochemicals and being non-toxic, have proven to impart better disease-fighting efficacies, thus leading to an increased focus on dietary interventions to both treat and prevent cancer. Owing to the complex interactions between their constituent phytochemicals, several dietary agents have been investigated for their therapeutic and preventive efficacies. However, due to lack of emphasis on confounding factors like bioavailability, absorption, metabolism, and excretion, essentially driven by phytocomplexity, incorporation of whole foods in therapeutic regimen has not been successful. This thesis exemplifies the need to investigate factors associated with the limitations in the current approach with respect to dietary agents. Bioactivity-guided fractionation of sweet potato greens extract (SPGE) led to the identification of ~100-fold more potent fraction in vitro. However, this efficacy could not be translated in vivo. We also studied whole ginger extract (GE) for its in vitro and in vivo prostate tumor growth-inhibitory and apoptosis-inducing effects. In addition, GE proved to be more efficacious as compared to its individual most-active constituents owing to the differences in their pharmacokinetic (PK) and bioavailability measurements. Hence, these studies emphasize the crucial role of synergistic/additive interactions among the constituents of whole foods in successful translation of their therapeutic benefits. Another factor that seeks further attention is the unique cellular mechanisms engaged by these phytochemicals to confer their remarkable effects. Phenolic compounds, the most-abundant of all phytochemicals, are well known for their antioxidant properties and act via reactive oxygen species (ROS)-mediated mechanisms. We however assert the underappreciated xenohormetic prooxidant role of phenolics, where cancer cell death is caused by induction of intolerable levels of ROS. We demonstrated that a Piper betel constituent, hydroxychavicol (HC), mediates cytotoxicity via ROS-induced DNA-damage. This thesis thus provides compelling grounds for future preclinical studies to validate their potential usefulness for cancer management

Uncovering New Links Through Interaction Duration

Link Prediction is the problem of inferring new relationships among nodes in a network that can occur in the near future. Classical approaches mainly consider neighborhood structure similarity when linking nodes. However, we may also want to take into account whether the two nodes we are going to link will benefit from that by having an active interaction over time. For instance, it is better to link two nodes � and � if we know that these two nodes will interact in the social network in the future, rather than suggesting �, who may never interact with �. Thus, the longer the interaction is estimated to last, i.e., persistent interactions, the higher the priority is for connecting the two nodes. This current thesis focuses on the problem of predicting how long two nodes will interact in a network by identifying potential pairs of nodes (�, �)that are not connected, yet show some Indirect Interaction. “Indirect Interaction” means that there is a particular action involving both the nodes depending on the type of network. For example, in social networks such as Facebook, there are users that are not friends but interact with other user’s wall posts. On the Wikipedia hyperlink network, it happens when readers navigate from page � to page � through the search box (on the top right corner of page �), and there is no explicit link on page � to �. This research explores cases that involved multiple interactions between � and � during an observational time interval [��, ��). Two supervised learning approaches are proposed for the problem. Given a set of network-based predictors, the basic approach consists of learning a binary classifier to predict whether or not an observed Indirect Interaction will last in the future. The second and more fine-grained approach consists of estimating how long the interaction will last by modeling the problem via Survival Analysis or as a Regression task. Once the duration is estimated, this information is leveraged for the Link Prediction task. Experiments were performed on the longitudinal Facebook network and wall interactions dataset, and Wikipedia Clickstream dataset to test this approach of predicting the Duration of Interaction and Link Prediction. Based on the experiments conducted, this study’s results show that the fine-grained approach performs the best with an AUROC of 85.4% on Facebook and 77% on Wikipedia for Link Prediction. Moreover, this approach beats a Link Prediction model that does not consider the Duration of Interaction and is based only on network properties, and that performs with an AUROC of 0.80 and 0.68 on Facebook and Wikipedia, respectively

Role of Simulations in Student Learning: A Case Study Using Marketing Simulation

Simulations, like other pedagogical tools, should be evaluated for their effectiveness in achieving course objectives and student learning. This research examines the efficiency of using a particular simulation in achieving course objectives and student learning compared with a general textbook and other learning pedagogical tools from the students’ perspective