Predictive Liability Models and Visualizations of High Dimensional Retail Employee Data

Employee theft and dishonesty is a major contributor to loss in the retail industry. Retailers have reported the need for more automated analytic tools to assess the liability of their employees. In this work, we train and optimize several machine learning models for regression prediction and analysis on this data, which will help retailers identify and manage risky employees. Since the data we use is very high dimensional, we use feature selection techniques to identify the most contributing factors to an employee's assessed risk. We also use dimension reduction and data embedding techniques to present this dataset in a easy to interpret format

Room-Temperature Processing of Inorganic Perovskite Films to Enable Flexible Solar Cells

Inorganic lead halide perovskite materials have attracted great attention recently due to their potential for greater thermal stability compared to hybrid organic perovskites. However, the high processing temperature to convert from the non-perovskite phase to cubic perovskite phase in many of these systems has limited their application in flexible optoelectronic devices. Here, we report a room temperature processed inorganic PSC based on CsPbI2Br as the light harvesting layer. By combing this composition with key precursor solvents, we show that the inorganic perovskite film can be prepared by the vacuum-assist method under room temperature conditions in air. Unencapsulated devices achieved the power conversion efficiency up to 8.67% when measured under 1-sun irradiation. Exploiting this room temperature process, flexible inorganic PSCs based on an inorganic metal halide perovskite material is demonstrated.Comment: 23 pages, 4 figures, and supplemental informatio

A centralized feedback control model for resource management in wireless networks

In a wireless environment, guaranteeing QoS is challenging because applications at multiple devices share the same limited radio bandwidth. In this paper we introduce and study a resource management model for centralized wireless networks, using feedback control theory. Before applying in practice, the proposed model is evaluated using the well-known 20-sim dynamic system simulator. The experimental results show that flexible and efficient resource allocation can be achieved for a variety of system parameters and WLAN scenarios; however, care should be taken in setting the control parameters and coefficients

Surfactant-aided exfoliation of molydenum disulphide for ultrafast pulse generation through edge-state saturable absorption

We use liquid phase exfoliation to produce dispersions of molybdenum disulphide (MoS2) nanoflakes in aqueous surfactant solutions. The chemical structures of the bile salt surfactants play a crucial role in the exfoliation and stabilization of MoS2. The resultant MoS2 dispersions are heavily enriched in single and few (<6) layer flakes with large edge to surface area ratio. We use the dispersions to fabricate free-standing polymer composite wide-band saturable absorbers to develop mode-locked and Q- switched fibre lasers, tunable from 1535-1565 and 1030-1070 nm, respectively. We attribute this sub-bandgap optical absorption and its nonlinear saturation behaviour to edge-mediated states introduced within the material band-gap of the exfoliated MoS2 nanoflakes.Comment: 6 pages, 5 figure

Control theory for principled heap sizing

We propose a new, principled approach to adaptive heap sizing based on control theory. We review current state-of-the-art heap sizing mechanisms, as deployed in Jikes RVM and HotSpot. We then formulate heap sizing as a control problem, apply and tune a standard controller algorithm, and evaluate its performance on a set of well-known benchmarks. We find our controller adapts the heap size more responsively than existing mechanisms. This responsiveness allows tighter virtual machine memory footprints while preserving target application throughput, which is ideal for both embedded and utility computing domains. In short, we argue that formal, systematic approaches to memory management should be replacing ad-hoc heuristics as the discipline matures. Control-theoretic heap sizing is one such systematic approach

Site selective reading of epigenetic markers by a dual-mode synthetic receptor array.

Variably functionalized self-folding deep cavitands form an arrayed, fluorescent indicator displacement assay system for the detection of post-translationally modified (PTM) histone peptides. The hosts bind trimethyllysine (KMe3) groups, and use secondary upper rim interactions to provide more sensitive discrimination between targets with identical KMe3 binding handles. The sensor array uses multiple different recognition modes to distinguish between miniscule differences in target, such as identical lysine modifications at different sites of histone peptides. In addition, the sensor is affected by global changes in structure, so it is capable of discriminating between identical PTMs, at identical positions on amino acid fragments that vary only in peptide backbone length, and can be applied to detect non-methylation modifications such as acetylation and phosphorylations located multiple residues away from the targeted binding site. The synergistic application of multiple variables allows dual-mode deep cavitands to approach levels of recognition selectivity usually only seen with antibodies