An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer set, and the firm decides the best subset to offer at any given moment to maximize expected revenue. The resulting dynamic program for the firm is intractable and approximated by a deterministic linear program called the CDLP which has an exponential number of columns. However, under the choice-set paradigm when the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has been proposed but finding an entering column has been shown to be NP-hard. In this paper, starting with a concave program formulation called SDCP that is based on segment-level consideration sets, we add a class of constraints called product constraints (σPC), that project onto subsets of intersections. In addition we propose a natural direct tightening of the SDCP called ESDCPκ, and compare the performance of both methods on the benchmark data sets in the literature. In our computational testing on the benchmark data sets in the literature, 2PC achieves the CDLP value at a fraction of the CPU time taken by column generation. For a large network our 2PC procedure runs under 70 seconds to come within 0.02% of the CDLP value, while column generation takes around 1 hour; for an even larger network with 68 legs, column generation does not converge even in 10 hours for most of the scenarios while 2PC runs under 9 minutes. Thus we believe our approach is very promising for quickly approximating CDLP when segment consideration sets overlap and the consideration sets themselves are relatively small

A Study on Leadership Styles Adopted at V-Trans in India

Leadership styles are usually considered a benefit for the most companies. This style focuses the management that provides guidance and help to its team and departments while accepting and receiving the inputs from individual team members. These leaders not reserve to their activities and authority only but in actual they bother about consultation of employees. To evaluated worker’s views of their senior and top leadership team and state that this style focuses on using the skills, experience, and ideas of others. However, the leaders or managers using this style but still remains the final decision making power in the leader’s hand. To his or her credits, they will not make major decision without firstly getting the input from those that will be affected, provide proper recognition, and delegate responsibilities. The main intension of this paper is to identify and examine the leadership styles adopted in the organization. This leadership styles improve the performance in both short term and long term and can be used for any type of work project

The Effects of Initial Dividend Announcements on Security Returns- Further Evidence

Daniel Walz is an Assistant Professor of Business Administration at Trinity University. Kalyan K. Roy is an Assistant Professor of Business Administration at the University of Calcutta

MICROANGIOGRAM VIDEO COMPRESSION USING ADAPTIVE PREDICTION

Coronary angiography is an X-ray examination of the heart\u27s arteries. This is an essential technique for diagnosis of heart damages. Image sequences from digital angiography contain areas of high diagnostic interest. Loss of information due to compression for regions of interest (ROI) in angiograms is not tolerable. Since Commercially available technology such as JPEG and MPEG do not satisfy medical requirements due to their severe blockartifacts. In this paper, a new compression algorithm that achieves high compression ratio and excellent reconstruction quality for video rate or sub-video rate angiograms is developed. The proposed algorithm exploits temporal spatial and spectral redundancies in backward adaptive fashion with Extremely low side information. An experimental result shows that the proposed scheme provides significant improvements in compression efficiencies

Protecting Children from Harmful Audio Content: Automated Profanity Detection From English Audio in Songs and Social-Media

A novel approach for the automated detection of profanity in English audio songs using machine learning techniques. One of the primary drawbacks of existing systems is only confined to textual data. The proposed method utilizes a combination of feature extraction techniques and machine learning algorithms to identify profanity in audio songs. Specifically, the approach employs the popular feature extraction techniques of Term frequency–inverse document frequency (TF-IDF), Bidirectional Encoder Representations from Transformers (BERT) and Doc2vec to extract relevant features from the audio songs. TF-IDF is used to capture the frequency and importance of each word in the song, while BERT is utilized to extract contextualized representations of words that can capture more nuanced meanings. To capture the semantic meaning of words in audio songs, also explored the use of the Doc2Vec model, which is a neural network-based approach that can extract relevant features from the audio songs. The study utilizes Open Whisper, an open-source machine learning library, to develop and implement the approach. A dataset of English audio songs was used to evaluate the performance of the proposed method. The results showed that both the TF-IDF and BERT models outperformed the Doc2Vec model in terms of accuracy in identifying profanity in English audio songs. The proposed approach has potential applications in identifying profanity in various forms of audio content, including songs, audio clips, social media, reels, and shorts

A homomorphism theorem and a Trotter product formula for quantum stochastic flows with unbounded coefficients

We give a new method for proving the homomorphic property of a quantum stochastic ow satisfying a quantum stochastic differential equation with unbounded coefficients, under some further hypotheses. As an application, we prove a Trotter product formula for quantum stochastic ows and obtain quantum stochastic dilations of a class of quantum dynamical semigroups generalizing results of [5

Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation

Photovoltaic (PV) system is one of the reliable alternative sources of energy and its contribution in energy sector is growing rapidly. The performance of PV system depends upon the solar insolation, which will be varying throughout the day, season and year. The biggest challenge is to obtain the maximum power from PV array at varying insolation levels. The maximum power point tracking (MPPT) controller, in association with tracking algorithm will act as a principal element in driving the PV system at maximum power point (MPP). In this paper, the simulation model has been developed and the results were compared for perturb and observe, incremental conductance, extremum seeking control and fuzzy logic controller based MPPT algorithms at different irradiation levels on a 10 KW PV array. The results obtained were analysed in terms of convergence rate and their efficiency to track the MPP.Keywords: Photovoltaic system, MPPT algorithms, perturb and observe, incremental conductance, scalar gradient extremum seeking control, fuzzy logic controller.Article History: Received 3rd Oct 2016; Received in revised form 6th January 2017; Accepted 10th February 2017; Available onlineHow to Cite This Article: Naick, B. K., Chatterjee, T. K. & Chatterjee, K. (2017) Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation. Int Journal of Renewable Energy Development, 6(1), 65-74.http://dx.doi.org/10.14710/ijred.6.1.65-7

Lymphomatoid granulomatosis masquerading as interstitial pneumonia in a 66-year-old man: a case report and review of literature

Abstract Lymphomatoid granulomatosis (LG) is a rare, Epstein-Barr virus (EBV)-associated systemic angiodestructive lymphoproliferative disorder that may progress to a diffuse large B cell lymphoma. Pulmonary involvement may mimic other more common lung pathologies including pneumonias. Therapeutic standards have not been established for LG, but rituximab, interferon-α2b (INF-α2b), and chemotherapy have shown to improve symptoms and long term prognosis. We report a case of rapid respiratory deterioration in a 66-year-old man with clinical presentation, chest radiography, pulmonary function testing and high resolution computed tomography (HRCT) findings consistent with idiopathic interstitial pneumonia, but very poor response to antibiotics and low dose steroids. Lung biopsy showed histopathology consistent with LG that was confirmed by a positive in situ hybridization for Epstein - Barr virus encoded RNA (EBER). The patient was treated with rituximab and combination chemotherapy and showed significant initial clinical improvement with gradual resolution of abnormal findings on imaging. However, the patient developed pancytopenia as a complication of chemotherapy and died secondary to septic shock and renal failure that were refractory to medical management. Autopsy showed diffuse alveolar damage but no evidence of any residual LG within the lungs. This case demonstrates that an open lung biopsy or video-assisted thoracoscopic surgical (VATS) biopsy is often necessary to rule out the presence of LG in order to determine the appropriate therapeutic strategy early in the course of illness to improve prognosis