Pengaruh Kualitas Pelayanan Terhadap Kepuasan Pelanggan Dan Konsekuensinya Pada Loyalitas (Studi Pada Obyek Wisata Di Kabupaten Malang)

Studi ini meneliti kepuasan wisatawan yang mengunjungi obyek wisata yang ada di Kabupaten Malang dengan menggunakan konsep dasar Swedish Customer Satisfaction Barometer (SCSB). Tujuan penelitian untuk menganalisis pengaruh langsung kualitas layanan (service quality) terhadap kepuasan wisatawan domestik (customer satisfaction), menganalisis pengaruh langsung harapan konsumen (customer expectation) terhadap kepuasan wisatawan domestik (customer satisfaction), dan menganalisis pengaruh langsung kepuasan konsumen (customer satisfaction) terhadap loyalitas konsumen (customer loyalty) wisatawan domestik. Sampel penelitian adalah wisatawan domestik yang berkunjung ke objek wisata (Pantai Sendang Biru, Pantai Ngliyep dan Pantai Bale Kambang), yaitu sebanyak 150 responden. Teknik analisis data yang digunakan adalah Structural Equation Modelling (SEM) dengan menggunakan bantuan program AMOS. Hasil penelitian menunjukkan bahwa ada pengaruh langsung antara kualitas layanan dan kepuasan pelanggan, tidak ada pengaruh yang signifikan anatara harapan dengan kepuasan pelanggan, ada pengaruh langsung antara kepuasan pelanggan dengan loyalitas konsumen. Variabel kualitas layanan yaitu reliability dan emphaty memiliki pengaruh yang paling besar terhadap kepuasan pelanggan sedangkan responsiveness, assurance, dan tangible memilki pengaruh yang cukup signifikan

A UTP semantics for communicating processes with shared variables and its formal encoding in PVS

CSP# (communicating sequential programs) is a modelling language designed for specifying concurrent systems by integrating CSP-like compositional operators with sequential programs updating shared variables. In this work, we define an observation-oriented denotational semantics in an open environment for the CSP# language based on the UTP framework. To deal with shared variables, we lift traditional event-based traces into mixed traces which consist of state-event pairs for recording process behaviours. To capture all possible concurrency behaviours between action/channel-based communications and global shared variables, we construct a comprehensive set of rules on merging traces from processes which run in parallel/interleaving. We also define refinement to check process equivalence and present a set of algebraic laws which are established based on our denotational semantics. We further encode our proposed denotational semantics into the PVS theorem prover. The encoding not only ensures the semantic consistency, but also builds up a theoretic foundation for machine-assisted verification of CSP# specifications.Full Tex

UPOCR: Towards Unified Pixel-Level OCR Interface

In recent years, the optical character recognition (OCR) field has been proliferating with plentiful cutting-edge approaches for a wide spectrum of tasks. However, these approaches are task-specifically designed with divergent paradigms, architectures, and training strategies, which significantly increases the complexity of research and maintenance and hinders the fast deployment in applications. To this end, we propose UPOCR, a simple-yet-effective generalist model for Unified Pixel-level OCR interface. Specifically, the UPOCR unifies the paradigm of diverse OCR tasks as image-to-image transformation and the architecture as a vision Transformer (ViT)-based encoder-decoder. Learnable task prompts are introduced to push the general feature representations extracted by the encoder toward task-specific spaces, endowing the decoder with task awareness. Moreover, the model training is uniformly aimed at minimizing the discrepancy between the generated and ground-truth images regardless of the inhomogeneity among tasks. Experiments are conducted on three pixel-level OCR tasks including text removal, text segmentation, and tampered text detection. Without bells and whistles, the experimental results showcase that the proposed method can simultaneously achieve state-of-the-art performance on three tasks with a unified single model, which provides valuable strategies and insights for future research on generalist OCR models. Code will be publicly available

Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation

This paper presents a comprehensive evaluation of the Optical Character Recognition (OCR) capabilities of the recently released GPT-4V(ision), a Large Multimodal Model (LMM). We assess the model's performance across a range of OCR tasks, including scene text recognition, handwritten text recognition, handwritten mathematical expression recognition, table structure recognition, and information extraction from visually-rich document. The evaluation reveals that GPT-4V performs well in recognizing and understanding Latin contents, but struggles with multilingual scenarios and complex tasks. Specifically, it showed limitations when dealing with non-Latin languages and complex tasks such as handwriting mathematical expression recognition, table structure recognition, and end-to-end semantic entity recognition and pair extraction from document image. Based on these observations, we affirm the necessity and continued research value of specialized OCR models. In general, despite its versatility in handling diverse OCR tasks, GPT-4V does not outperform existing state-of-the-art OCR models. How to fully utilize pre-trained general-purpose LMMs such as GPT-4V for OCR downstream tasks remains an open problem. The study offers a critical reference for future research in OCR with LMMs. Evaluation pipeline and results are available at https://github.com/SCUT-DLVCLab/GPT-4V_OCR

Capacity Optimization Based on Energy Storage to Restrain Severe Fluctuation of Wind Power

In order to solve the coordination problem between the economy and the stabilization effect of energy storage system, a capacity optimization model based on energy storage to suppress the violent fluctuation of wind power is proposed, and a multi-objective function with the maximum wind power dissipation capacity and the minimum operating cost of energy storage system is established. Considering the average annual cost and penalty cost of the whole life cycle, an evaluation index with correlation coefficient as the fitting degree is proposed, and the reference power of wind farm grid connection is optimized by particle swarm algorithm. Using the operation data of Qidong Wind Farm in Jiangsu Province, the theoretical validity is verified, the coordination is improved to the greatest extent, and the capacity demand for energy storage system is reduced

Production of a Monoclonal Antibody for the Detection of Forchlorfenuron: Application in an Indirect Enzyme-Linked Immunosorbent Assay and Immunochromatographic Strip

In this study, a monoclonal antibody (mAb) specific to forchlorfenuron (CPPU) with high sensitivity and specificity was produced and designated (9G9). To detect CPPU in cucumber samples, an indirect enzyme-linked immunosorbent assay (ic-ELISA) and a colloidal gold nanobead immunochromatographic test strip (CGN-ICTS) were established using 9G9. The half-maximal inhibitory concentration (IC50) and the LOD for the developed ic-ELISA were determined to be 0.19 ng/mL and 0.04 ng/mL in the sample dilution buffer, respectively. The results indicate that the sensitivity of the antibodies prepared in this study (9G9 mAb) was higher than those reported in the previous literature. On the other hand, in order to achieve rapid and accurate detection of CPPU, CGN-ICTS is indispensable. The IC50 and the LOD for the CGN-ICTS were determined to be 27 ng/mL and 6.1 ng/mL. The average recoveries of the CGN-ICTS ranged from 68 to 82%. The CGN-ICTS and ic-ELISA quantitative results were all confirmed by liquid chromatography—tandem mass spectrometry (LC-MS/MS) with 84–92% recoveries, which indicated the methods developed herein are appropriate for detecting CPPU in cucumber. The CGN-ICTS method is capable of both qualitative and semiquantitative analysis of CPPU, which makes it a suitable alternative complex instrument method for on-site detection of CPPU in cucumber samples since it does not require specialized equipment

Recent Advances in Rapid Detection Techniques for Pesticide Residue: A Review

As an important chemical pollutant affecting the safety of agricultural products, the on-site and efficient detection of pesticide residues has become a global trend and hotspot in research. These methodologies were developed for simplicity, high sensitivity, and multiresidue detection. This review introduces the currently available technologies based on electrochemistry, optical analysis, biotechnology, and some innovative and novel technologies for the rapid detection of pesticide residues, focusing on the characteristics, research status, and application of the most innovative and novel technologies in the past 10 years, and analyzes challenges and future development prospects. The current review could be a good reference for researchers to choose the appropriate research direction in pesticide residue detection

The neuroprotective effect of curcumin in a mouse model of Parkinson’s disease and its mechanism

Objective To investigate the neuroprotective effect of curcumin on mice with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinson’s disease (PD) and its mechanism. Methods A total of 72 male C57BL/6J mice were randomly divided into control group (group A), MPTP group (group B), and MPTP+curcumin group (group C). For the 5 d before the experiment, the mice in groups B and C were given intraperitoneal injection of MPTP every day, and those in group A were given intraperitoneal injection of an equal volume of normal saline; since day 6, the mice in group C were given intraperitoneal injection of curcumin dissolved in DMSO at a dose of 50 mg/kg, and those in groups A and B were given intraperitoneal injection of an equal volume of DMSO, every day for 7 consecutive days. After the end of administration, behavioral experiments were used to evaluate the motor, learning, and memory functions of mice in each group. On day 15 of the experiment, the samples of substantia nigra were collected from the mice in each group, and ELISA was used to measure the content of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6); Western blotting was used to measure the relative content of CD86 and NF-κB; immunohistochemical staining was used to measure the number of TH-positive neurons. Results Compared with group B, groups A and C had a significant reduction in descending time, significant increases in drop latency and percentage of alternation (F=17.29-19.28,P<0.05), significant reductions in the content of TNF-α, IL-1β, and IL-6 (F=31.73-80.97,P<0.05) and the expression of CD86 and NF-κB in the substantia nigra (F=24.93,55.61,P<0.05), and a significant increase in the number of TH-positive neurons in the substantia nigra (F=47.64,P<0.05). Conclusion Curcumin can effectively improve behavior disorder and exert a neuroprotective effect in PD mice, possibly by inhibiting the NF-κB signaling pathway, thereby leading to the inhibition of microglial cell activation, the reduction in inflammatory response, and the alleviation of dopaminergic neuron degeneration