Research on Vehicle Scheduling of Cross-Regional Collection Using Hierarchical Agglomerative Clustering and Algorithm Optimization

At present, municipal solid waste (MSW) collection is based on the divide-regional operation mode, which has many deficiencies. This paper proposes a cross-regional operation scheme. Through the initial assignment, type labeling, and reassignment, and use the improved hierarchical agglomerative clustering (IHAC) algorithm and garbage collecting route optimization (GCRO) algorithm to realize intelligent allocation of garbage and scheduling route planning of collection vehicles. The experimental results demonstrate the proposed scheme improves the utilization of vehicle resources, reduces the operating cost, realizes the balanced allocation of garbage, and solves the problems caused by limitations of the original operation scheme, which demonstrates the feasibility and effectiveness of the cross-regional operation.

TEACHING WRITING RECOUNT TEXT AT EIGHT GRADE USING THINK-TALK-WRITE TECHNIQUE BY DIGITAL STORYTELLING

Based on the fact that the students writing ability, was very low, so the students had difficulties in writing especially writing recount text. The aims of this research to find out: 1) The implementation of the scenario in teaching English writing recount text using think-talk-write technique by digital storytelling 2) The students difficulties in learning writing recount text using think-talk-write technique by digital storytelling. This study used descriptive qualitative research. The subject of the study was the eight grade students in one of junior high school that consist of twenty students. The instrument used in this study were observation sheet and questionnaire. The results of this study indicated that the implementation of teaching and learning process was done in accordance with the scenario that had been made by the researcher. The initial assignment was given to the students to know what are the difficulties faced by the students. Based on the result, it could be mentioned that the students difficulties were the use of grammar, poor vocabulary-especially in spelling and how to use appropriate vocabulary. After learning using the TTW technique, the students could overcome their difficulties. They could understand better the use of grammar and structure, appropriate vocabulary and better in spelling. Keywords: Think-Talk-Write, Digital Storytelling, Writing

Improving WalkSAT for Random 3-SAT Problems

Stochastic local search (SLS) algorithms are well known for their ability to efficiently find models of random instances of the Boolean satisfiability (SAT) problems. One of the most famous SLS algorithms for SAT is called WalkSAT, which has wide influence and performs well on most of random 3-SAT instances. However, the performance of WalkSAT lags far behind on random 3-SAT instances equal to or greater than the phase transition ratio. Motivated by this limitation, in the present work, firstly an allocation strategy is introduced and utilized in WalkSAT to determine the initial assignment, leading to a new algorithm called WalkSATvav. The experimental results show that WalkSATvav significantly outperforms the state-of-the-art SLS solvers on random 3-SAT instances at the phase transition for SAT Competition 2017. However, WalkSATvav cannot rival its competitors on random 3-SAT instances greater than the phase transition ratio. Accordingly, WalkSATvav is further improved for such instances by utilizing a combination of an improved genetic algorithm and an improved ant colony algorithm, which complement each other in guiding the search direction. The resulting algorithm, called WalkSATga, is far better than WalkSAT and significantly outperforms some previous known SLS solvers on random 3-SAT instances greater than the phase transition ratio from SAT Competition 2017. Finally, a new SAT solver called WalkSATlg, which combines WalkSATvav and WalkSATga, is proposed, which is competitive with the winner of random satisfiable category of SAT competition 2017 on random 3-SAT problem.

ENTITLEMENT THEORY OF JUSTICE AND END-STATE FAIRNESS IN THE ALLOCATION OF GOODS

Robert Nozick allegedly introduced his liberal theory of private ownership as an objection to theories of end-state justice. Nevertheless, we show that, in a stylized framework for the allocation of goods in joint ventures, both approaches can be seen as complementary. More precisely, in such a context, self-ownership (the basis for Nozick’s entitlement theory of justice) followed by voluntary transfer (Nozick’s principle of just transfer) can lead to end-state fairness (as well as Pareto efficiency). Furthermore, under a certain solidarity condition, the only way to achieve end-state fairness, following Nozick’s procedure, is to endorse an egalitarian rule for the initial assignment of rights.

Towards Next Generation Rubrics: An Automated Assignment Feedback System

As the use of blended learning environments and digital technologies become integrated into the higher education sector, rich technologies such as analytics have shown promise in facilitating teaching and learning. One popular application of analytics is Automated Writing Evaluation (AWE) systems. Such systems can be used in a formative way; for example, by providing students with feedback on digitally submitted assignments. This paper presents work on the development of an AWE software tool for an Australian university using advanced text analytics techniques. The tool was designed to provide students with timely feedback on their initial assignment drafts, for revision and further improvement. Moreover, it could also assist academics in better understanding students’ assignment performance so as to inform future teaching activities. The paper provides details on the methodology used for development of the software, and presents the results obtained from the analysis of text-based assignments submitted in two subjects. The results are discussed, highlighting how the tool can provide practical value, followed by insights into existing challenges and possible future directions.

Effect of NO2 substitution and solvent on UV-visible spectra, redox potentials and electron transfer mechanisms of copper β-nitrotriarylcorroles. Proposed electrogeneration of a Cu(I) oxidation state

Three copper triarylcorroles containing a [Formula: see text]-pyrrole nitro substituent were synthesized and characterized as to their spectral and electrochemical properties in nonaqueous media. The examined compounds are represented as [Formula: see text]-NO2(YPh)3CorCu, where Cor is the trianion of a triphenylcorrole and Y is a Cl, H or CH3 substituent at the para-position of the three meso-phenyl rings of the compound. The data from absorption spectra, electrochemistry and thin-layer spectroelectrochemistry are consistent with an initial assignment of Cu[Formula: see text]-Cor[Formula: see text] in CH2Cl2, DMF and pyridine and electrogeneration of a formal Cu(II) corrole with an unreduced macrocycle, represented as Cu[Formula: see text]-Cor[Formula: see text], after the first one-electron reduction in these solvents. The doubly reduced [Formula: see text]-nitrocorrole has a sharp Soret band at 439 nm and a well-defined Q-band at 611 nm in CH2Cl2. Similar absorption spectra are seen for the three examined doubly reduced nitrocorroles in DMF and pyridine, suggesting formation of a Cu(I) species with an unreduced macrocycle which is represented as Cu[Formula: see text]-Cor[Formula: see text]. Changes in redox potentials and absorption spectra of the nitrocorroles are examined as a function of solvent and substituents on the meso-phenyl rings of the compounds and comparisons are made between spectral and electrochemical data of the newly synthesized corroles and that of structurally related tetraarylcorroles lacking a [Formula: see text]-nitro group.

Performance Comparison of Hybrid Electromagnetism-Like Mechanism Algorithms with Descent Method

Electromagnetism-like Mechanism (EM) method is known as one of metaheuristics. The basic idea is one that a set of parameters is regarded as charged particles and the strength of particles is corresponding to the value of the objective function for the optimization problem. Starting from any set of initial assignment of parameters, the parameters converge to a value including the optimal or semi-optimal parameter based on EM method. One of its drawbacks is that it takes too much time to the convergence of the parameters like other meta-heuristics. In this paper, we introduce hybrid methods combining EM and the descent method such as BP, k-means and FIS and show the performance comparison among some hybrid methods. As a result, it is shown that the hybrid EM method is superior in learning speed and accuracy to the conventional methods.